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Read the full journal, including this article, by downloading the PDF below. Image credit: AI-generated illustration produced with OpenAI (DALL·E), 2026. by Prof Wynand Goosen Abstract The rapid diffusion of generative artificial intelligence (AI) across education, professional practice, and decision-making has transformed human reasoning into a hybrid process in which humans and machines jointly generate interpretations, judgments, and knowledge claims. While critical thinking is widely promoted as a safeguard against automation bias and uncritical reliance on AI outputs, growing empirical and theoretical evidence suggests that critical thinking alone is insufficient in AI-mediated environments. Instead, effective reasoning depends on metacognition, the monitoring, regulation, and evaluation of one’s own cognitive processes, extended to include reflection on machine-generated contributions (Flavell, 1979; Dunlosky & Metcalfe, 2009). Metacognition implies thinking on an extended basis. This extended basis identifies “consequence” as the missing link. Understanding the real impact of any form of thinking, whether originating from natural humans or artificial intelligence. This article reconceptualises metacognition as secondary thinking: a supervisory cognitive layer that governs how humans engage with, evaluate, and rely on AI systems. Drawing on cognitive psychology, education, human–computer interaction, and decision sciences, the paper argues that secondary thinking is the central mechanism through which epistemic agency, trust calibration, and responsibility are maintained in human–AI reasoning (Parasuraman & Riley, 1997; Liao & Sundar, 2022). Three core claims are advanced. First, generative AI shifts cognition from an individual activity to a distributed human–machine system, intensifying the need for metacognitive regulation (Hutchins, 1995; Hollan et al., 2000). Second, critical thinking in AI-supported contexts is contingent on secondary thinking, which determines when and how analytical evaluation is activated (Bjork et al., 2013; Halpern, 2014). Third, failures of secondary thinking explain phenomena such as automation bias, cognitive offloading, and over-trust in fluent AI outputs (Skitka et al., 2000; Kasneci et al., 2023). The article establishes a conceptual foundation for understanding secondary thinking as a mediator between machine cognition and human judgment, preparing the ground for a structured literature survey and the development of an integrative Human–AI Metacognitive Mediation (HAMM) model in subsequent sections. Keywords: Metacognition; Secondary Thinking; Critical Thinking; Human–AI Collaboration; Generative Artificial Intelligence; Distributed Cognition; Automation Bias; AI Literacy 1. Introduction: From Individual Cognition to Hybrid Human–AI Reasoning The integration of generative artificial intelligence (AI) into everyday cognitive work has fundamentally altered how reasoning is performed across educational, professional, and organisational contexts. Tasks such as writing, analysing information, planning, problem-solving, and decision-making now increasingly involve sustained interaction with AI systems capable of producing fluent, context-sensitive, and seemingly reasoned outputs. These systems do not merely support cognition at the margins or automate routine functions; rather, they participate directly in the generation, structuring, and evaluation of ideas. In many contemporary settings, AI-generated outputs function as primary cognitive inputs, the starting point for reasoning rather than its endpoint, thereby reshaping how judgments are formed. As a consequence, cognition can no longer be adequately understood as a purely internal process confined to the individual mind. Instead, reasoning unfolds within hybrid human–machine systems, in which cognitive labour is distributed across human intuitions, analytical processes, and machine-generated contributions (Salomon, 1993; Hutchins, 1995; Kirsh, 2010). Within such systems, reasoning outcomes (consequences) emerge not from isolated human deliberation or automated computation alone, but from the interaction between fast human judgments, AI-generated outputs, and the regulatory processes that govern their integration. The consequences, or impact, of the integrated human and artificial thinking suggest a level of “metacognition” —thinking in such a way that we understand the real consequences. This reconceptualisation is consistent with foundational work in distributed cognition, which demonstrates that reasoning routinely extends beyond the individual to include artefacts, representations, technologies, and social structures that shape how problems are framed and solved (Salomon, 1993; Hutchins, 1995). Generative AI intensifies this dynamic by functioning not only as an external resource but as an active contributor to reasoning, proposing arguments, synthesising evidence, generating counterfactuals, and simulating inferential pathways. In practice, humans increasingly co-think with AI systems, engaging them as interlocutors within cognitive activity rather than as neutral tools executing predefined instructions. This shift fundamentally alters the epistemic conditions under which reasoning occurs. When AI systems contribute directly to the content and structure of reasoning, questions of agency, responsibility, authorship, and justification become distributed rather than singular. The apparent coherence, confidence, and completeness of AI-generated outputs can obscure their probabilistic and non-semantic foundations, while their speed and scale can reduce opportunities for reflective human oversight. As a result, epistemic risk no longer arises solely from human bias or error, but from mismanaged interaction between human judgment and machine-generated contributions. Against this backdrop, a foundational epistemic question emerges: What forms of thinking enable humans to remain responsible epistemic agents when reasoning with and through AI? In educational and professional discourse, critical thinking is commonly positioned as the primary response to this challenge (Facione, 2015; Ennis, 2016). Learners and practitioners are urged to evaluate AI outputs, interrogate assumptions, verify sources, and resist uncritical acceptance. While normatively compelling, this response implicitly assumes that critical thinking is continuously available and readily activated. However, extensive research in cognitive psychology demonstrates that critical thinking is effortful, situational, and conditionally deployed, rather than a default mode of reasoning (Kuhn, 1999; Halpern, 2014). Analytical evaluation requires sustained attention and cognitive control, and it is frequently not activated in environments characterised by time pressure, informational overload, or reduced perceived effort. When tasks appear fluent, complete, or cognitively efficient, as is often the case with generative AI outputs, individuals are more likely to rely on surface plausibility than on sustained analytical scrutiny. Empirical evidence further indicates that analytical reasoning is governed by higher-order regulatory processes rather than operating autonomously. Individuals do not engage in continuous critical evaluation; instead, such evaluation is triggered by signals of uncertainty, contradiction, or epistemic risk. In the absence of these signals, even highly trained individuals may accept outputs unreflectively, particularly when those outputs align with prior beliefs or expectations. AI-mediated environments systematically attenuate many of the cues that typically prompt scrutiny—such as visible uncertainty, hesitation, or partial explanations—thereby increasing the likelihood that critical thinking remains dormant. These regulatory processes are captured by metacognition, broadly defined as awareness and control of one’s own thinking (Flavell, 1979; Nelson & Narens, 1990). Metacognition enables individuals to monitor uncertainty, evaluate progress, and adjust cognitive strategies. In AI-mediated reasoning, however, metacognition must operate at an expanded scope. It must regulate not only human thought processes, but also reliance on machine-generated outputs, including decisions about when to accept, interrogate, override, or suspend AI assistance (Liao & Sundar, 2022). Despite this necessity, research on metacognition, critical thinking, and human–AI interaction remains fragmented. Educational psychology has developed robust models of self-regulation yet typically treats cognition as individual (Schraw & Dennison, 1994). Human–AI interaction research has focused extensively on usability, trust, and performance, but with limited integration of metacognitive theory (Parasuraman et al., 2000). Meanwhile, educational discussions of generative AI often frame critical thinking as a static skill to be preserved, rather than as a conditionally activated process governed by metacognitive mediation (Holmes et al., 2023). This fragmentation obscures a central insight: failures in human–AI reasoning are frequently not failures of critical thinking capacity, but failures of metacognitive regulation within hybrid systems. When regulatory oversight is weak, critical thinking may never be activated, regardless of an individual’s expertise or intent. This article addresses that gap by advancing secondary thinking as the supervisory mechanism that mediates between human cognition and machine-generated contributions. Building on this insight, the article proposes the Human–AI Metacognitive Mediation (HAMM) model, which conceptualises reasoning in AI-mediated environments as a multi-layered, recursively regulated system. Within this model, secondary thinking governs the activation of critical thinking, the calibration of trust in AI systems, and the integration of machine outputs into human judgment. By foregrounding metacognitive mediation, the HAMM model provides a coherent theoretical foundation for understanding epistemic agency, accountability, and responsible reasoning in the age of generative AI. 2. Metacognition as Secondary Thinking Metacognition has long been defined as “knowledge and cognition about cognitive phenomena”, encompassing the processes by which individuals plan, monitor, and regulate their thinking (Flavell, 1979). This foundational formulation established that cognition is not limited to first-order processes such as perception, inference, or memory retrieval, but also includes higher-order awareness of how those processes unfold and how effectively they serve one’s goals. Subsequent theoretical models refined this view by distinguishing between metacognitive knowledge, metacognitive monitoring, and metacognitive control, emphasising that effective reasoning depends not only on the content of thought, but on the continuous oversight and regulation of cognitive activity (Nelson & Narens, 1990; Schraw & Dennison, 1994; Efklides, 2008). Across decades of empirical research, metacognition has been shown to predict learning quality, problem-solving success, and error detection across a wide range of domains and age groups. Importantly, these effects are most pronounced in complex, uncertain, or ill-structured task contexts in which individuals must decide not only how to think, but whether their current understanding is adequate and when to revise their approach (Zimmerman, 2002; Dunlosky & Metcalfe, 2009). These characteristics closely resemble the cognitive demands imposed by AI-mediated reasoning environments. In this article, metacognition is conceptualised functionally as secondary thinking—a supervisory layer of cognition that operates on thinking rather than as thinking. This distinction is analytically important. Secondary thinking does not directly generate ideas, arguments, or solutions; instead, it governs the conditions under which such cognitive products are produced, evaluated, and revised. Framed in this way, secondary thinking functions as a form of cognitive governance, shaping the reliability, depth, and epistemic quality of reasoning rather than its immediate outputs. More specifically, secondary thinking regulates cognition through several interrelated functions. It involves monitoring the coherence, plausibility, and uncertainty of one’s own reasoning, allowing individuals to recognise gaps in understanding or mismatches between confidence and justification (Schraw, 1998; Dunlosky & Metcalfe, 2009). It also includes evaluating the reliability, scope, and limitations of AI-generated outputs, particularly in light of the probabilistic and opaque nature of generative models (Van den Bosch & Bronkhorst, 2018; Liao & Sundar, 2022). A further function of secondary thinking is detecting cognitive conflict, such as discrepancies between intuitive judgments and analytical considerations, or between human reasoning and machine suggestions (Kahneman, 2011; Stanovich et al., 2016). Finally, secondary thinking supports strategic control, enabling individuals to decide when to rely on AI, when to override it, and when to seek alternative sources or verification (Parasuraman et al., 2000; Endsley, 2017). This framing clarifies the role of metacognition in AI-mediated reasoning. Rather than treating metacognition as a generic learning skill or background trait, secondary thinking is understood as a dynamic regulatory mechanism that governs the interaction between human cognition and machine cognition. It operates above both intuitive, fast processes and deliberate analytical processes, coordinating their deployment in response to contextual demands and epistemic risk (Bjork et al., 2013). Crucially, secondary thinking is not automatically triggered. Its activation depends on task design, perceived stakes, time pressure, and the presence of explicit reflective cues. In environments where AI systems produce fluent, confident, and seemingly authoritative outputs, the absence of such cues can suppress secondary thinking altogether. Under these conditions, even highly educated individuals may accept outputs uncritically, mistaking coherence, confidence, or stylistic sophistication for epistemic correctness (Williams et al., 2022). This vulnerability underscores the central importance of secondary thinking in hybrid human–AI reasoning systems. 3. Critical Thinking in AI-Mediated Contexts Critical thinking is typically defined as purposeful, reflective judgment involving the analysis and evaluation of arguments, evidence, and assumptions (Facione, 1990; Ennis, 2016). Within higher education and professional practice, it is widely regarded as a cornerstone competence, underpinning informed decision-making, complex problem-solving, ethical judgment, and responsible participation in knowledge-based societies. Critical thinking is often positioned as a safeguard against error, bias, and misinformation, particularly in environments characterised by informational abundance, competing claims, and epistemic uncertainty. In policy discourse and educational reform, it is frequently presented as the primary defence against the epistemic risks associated with digital technologies and automated systems. However, a substantial body of research demonstrates that critical thinking is neither context-free nor continuously active. Rather than operating as a default cognitive mode, critical thinking is situational, effortful, and strongly shaped by higher-order regulatory processes that govern attention, effort allocation, and strategy selection (Halpern, 2014; Kuhn, 2015). Individuals do not constantly evaluate the quality of information they encounter. Instead, analytical reasoning is selectively engaged in response to cues such as uncertainty, perceived risk, contradiction, or explicit demands for justification. When these cues are absent, even well-trained individuals may rely on surface plausibility rather than deliberate evaluation. From a cognitive perspective, critical thinking requires sustained attention, effortful processing, and the inhibition of intuitive or habitual responses. These demands make it cognitively costly and therefore selectively deployed. Individuals are more likely to engage in critical scrutiny when they perceive high stakes or epistemic danger, and less likely to do so when tasks appear familiar, efficient, or well-structured. Consequently, critical thinking is highly sensitive to features of the surrounding cognitive environment, including time pressure, perceived task difficulty, motivational factors, and the availability of external cognitive supports. Environments that reduce effort or signal completion can unintentionally suppress analytical engagement. In AI-supported environments, this conditionality becomes especially pronounced. Generative AI systems can, under appropriate conditions, scaffold critical thinking by exposing users to alternative perspectives, counterarguments, illustrative examples, and structured explanations that prompt comparison, evaluation, and synthesis (Chi, 2009; Kerrigan & Azevedo, 2022). When AI is used dialogically and reflectively—through iterative prompting, critique, explanation requests, or justification cycles—it can function as a cognitive partner that extends rather than replaces human reasoning capacity. Empirical work suggests that such reflective use of AI can enhance argument quality, conceptual integration, and depth of understanding, particularly when users remain actively engaged in evaluating the AI’s contributions (Xie et al., 2024). At the same time, generative AI can suppress critical thinking, particularly when its outputs are fluent, confident, and presented as complete or authoritative solutions. In these cases, AI reduces perceived task difficulty and creates an impression that cognitive work has already been done, encouraging cognitive offloading and premature closure (Kasneci et al., 2023). This suppression is amplified by well-established cognitive biases, most notably the tendency to equate linguistic fluency with epistemic reliability (Kahneman, 2011). As Bender and Koller (2020) argue, the surface coherence of language-model outputs can obscure underlying inaccuracies, fabrications, or unsupported inferences, creating a powerful illusion of understanding that discourages further scrutiny. Importantly, in such cases, critical thinking is not absent because users lack the relevant skills, dispositions, or educational preparation. Rather, it is absent because it is never activated. The cognitive environment created by generative AI often removes or attenuates the signals—such as visible uncertainty, hesitation, partial reasoning, or error—that typically prompt analytical evaluation. Without these epistemic triggers, individuals may default to acceptance, particularly when AI outputs align with prior beliefs, expectations, or goals. As a result, critical thinking remains latent, even among individuals with substantial training and experience in analytical reasoning and professional judgment. These observations indicate that critical thinking alone cannot adequately explain reasoning quality in AI-mediated contexts. Instead, critical thinking is governed by secondary thinking, which determines when analytical evaluation is warranted, how intensively it should be applied, and whether AI outputs should be accepted, questioned, or rejected (Dunlosky & Metcalfe, 2009; Bjork et al., 2013). Secondary thinking monitors epistemic risk, detects overconfidence, and initiates reflective scrutiny when conditions demand it. Without such metacognitive oversight, critical thinking cannot reliably fulfil its epistemic function within hybrid cognitive systems, regardless of an individual’s formal competence, experience, or intentions. 4. Machine Cognition, Automation Bias, and Distributed Responsibility Although contemporary AI systems do not possess cognition in the human sense, they increasingly perform functions that simulate the outward characteristics of reasoning. These include generating explanations, synthesising large bodies of information, identifying patterns across datasets, and proposing decisions or action pathways that resemble deliberative judgment (Miller, 2019; Bender et al., 2021). In interactive contexts, these outputs are linguistically fluent, context-sensitive, and often structurally indistinguishable from human-authored reasoning. They follow the conventions of argumentation, explanation, and narrative coherence that humans associate with understanding and rational agency. As a result, users frequently respond to AI systems as if they were epistemic agents—entities capable of knowing, reasoning, and justifying—rather than as computational artefacts executing statistical inference. This functional resemblance has profound cognitive consequences. Humans are evolutionarily and socially predisposed to attribute understanding, intention, and authority to entities that produce coherent language and plausible explanations. Language fluency, in particular, acts as a powerful cue for competence and trustworthiness. In the case of generative AI, this attribution occurs despite extensive evidence that such systems operate through probabilistic pattern completion rather than semantic comprehension, intentional reasoning, or truth-directed inference (Bender & Koller, 2020; Ji et al., 2023). The system does not “know” what it states, nor does it possess commitments to truth, evidence, or justification. The growing disjunction between epistemic appearance and epistemic reality therefore becomes a central source of risk in AI-mediated reasoning. Crucially, the problem is not simply that users misunderstand how AI systems work at a technical level. Rather, AI systems actively reshape the epistemic environment in which judgments are formed. Generative AI reduces informational friction by presenting outputs that are immediate, confident, syntactically complete, and often framed as solutions rather than as provisional suggestions. Traditional cues that signal uncertainty—hesitation, partial explanations, visible effort, acknowledged gaps, or expressions of doubt—are largely absent. This absence alters the cognitive ecology of reasoning, shifting users toward acceptance rather than interrogation. Even when errors or inconsistencies are present, the smoothness of presentation can suppress the impulse to scrutinise. One of the most robustly documented consequences of this altered epistemic environment is automation bias, defined as the systematic tendency to over-rely on automated systems, particularly when they appear authoritative, consistent, or cognitively efficient (Parasuraman & Riley, 1997; Skitka et al., 2000). Research across aviation, healthcare, finance, and military decision-making consistently demonstrates that individuals frequently defer to automated recommendations even when contradictory evidence is available or when the system is demonstrably fallible. Importantly, automation bias persists among experts and does not reliably diminish with experience alone, especially under conditions of cognitive load, time pressure, or task complexity (Mosier & Skitka, 2018). In AI-mediated reasoning, automation bias manifests in distinct but related forms. Users may accept AI-generated explanations without verification, fail to notice hallucinated citations or fabricated claims, or defer judgment to the system when outputs align with prior beliefs or goals. Generative AI intensifies these effects by masking epistemic uncertainty behind linguistic fluency, thereby exploiting well-known cognitive heuristics that equate coherence with correctness (Kahneman, 2011). The result is not blind trust in technology per se, but a subtle recalibration of epistemic vigilance in which scrutiny is deferred unless explicitly triggered. A key construct for understanding these dynamics is trust calibration, defined as the alignment between a user’s confidence in an AI system and the system’s actual reliability in a given context (Van den Bosch & Bronkhorst, 2018; Liao & Sundar, 2022). Miscalibrated trust produces two symmetrical failure modes: over-reliance, in which erroneous or inappropriate outputs are accepted, and under-reliance, in which valuable assistance is dismissed or ignored. Importantly, trust calibration is not achieved solely through improvements in system accuracy, transparency, or explainability. It is fundamentally a metacognitive accomplishment, requiring users to recognise uncertainty, reflect on system limitations, assess contextual appropriateness, and dynamically adjust reliance strategies (Gigerenzer, 2020). From the perspective of distributed cognition, reasoning outcomes remain human responsibilities, even when machines contribute substantially to the cognitive process (Hutchins, 1995). Cognitive artefacts can extend, scaffold, and transform reasoning by externalising memory, generating representations, or accelerating comparison. However, they do not assume epistemic agency. The delegation of cognitive labour—such as information retrieval or synthesis—does not entail the delegation of epistemic accountability. Decisions, interpretations, and justifications ultimately remain attributable to human agents. Ethical and epistemic responsibility therefore cannot be offloaded to machines, regardless of their apparent sophistication or autonomy. Within this distributed cognitive system, secondary thinking emerges as the mechanism through which responsibility is exercised and maintained. Secondary thinking governs how AI outputs are interpreted, how trust is dynamically calibrated, and how final judgments are justified and defended. It enables users to step back from fluent outputs, interrogate their reliability, and reflect on how machine-generated content has shaped their reasoning process. By regulating the interaction between human judgment and machine-generated contributions, secondary thinking supports epistemic vigilance, accountability, and adaptive reliance within hybrid human–AI reasoning systems (Fricker, 2007; Medina, 2013). 5. Synthesis of the Literature: Secondary Thinking as a Mediator in Human–AI Reasoning The preceding sections establish three interlocking premises that together reframe how reasoning must be understood in AI-mediated contexts. First, cognition in AI-rich environments is increasingly distributed across human and machine agents, rather than confined to the individual mind. Second, critical thinking—while indispensable to sound judgment—does not operate continuously or autonomously in such environments; its activation is conditional and effortful. Third, metacognitive regulation, conceptualised in this article as secondary thinking, is required to govern reasoning processes within hybrid cognitive systems. This section synthesises findings across educational psychology, cognitive science, and human–AI interaction research to demonstrate that secondary thinking operates not merely as an auxiliary skill, but as a mediating mechanism that determines how machine-generated contributions influence human judgment. Within educational psychology, decades of empirical research consistently demonstrate that metacognition is a stronger predictor of learning quality, error detection, transfer, and long-term retention than cognitive ability or domain knowledge alone (Schraw & Dennison, 1994; Zimmerman, 2002; Dunlosky & Metcalfe, 2009). Learners with strong metacognitive skills are better able to monitor their understanding, detect misconceptions, allocate effort strategically, and adapt their approaches when faced with difficulty. These advantages are especially pronounced in ill-structured problem-solving contexts, where there is no single correct solution path and where success depends on evaluating the adequacy and reliability of one’s reasoning strategies (Efklides, 2008). In such contexts, progress hinges less on executing procedures and more on regulating cognition itself. Crucially, these metacognitive advantages are not limited to formal learning settings. They generalise to any environment characterised by uncertainty, complexity, and incomplete information—conditions that closely resemble contemporary AI-mediated reasoning contexts. Generative AI systems introduce precisely the circumstances under which metacognitive regulation becomes essential: informational abundance, reduced cognitive effort, and asymmetric epistemic authority between human users and machine-generated outputs. When AI systems rapidly generate fluent explanations, summaries, or recommendations, users must decide not only what to accept, but whether acceptance is warranted at all. These decisions are inherently metacognitive. Parallel insights emerge from the literature on human–automation interaction and decision sciences. Decades of research on automation bias demonstrate that individuals frequently over-rely on automated systems, even when those systems are demonstrably fallible or when contradictory evidence is available (Parasuraman & Riley, 1997; Skitka et al., 2000). This over-reliance is exacerbated under conditions of cognitive load, time pressure, or perceived system authority, and persists even among highly trained professionals (Mosier & Skitka, 2018). Importantly, these failures cannot be adequately explained by lack of expertise, motivation, or training. Instead, they reflect breakdowns in metacognitive monitoring, particularly failures to recognise uncertainty, question reliability, or recalibrate trust in light of contextual cues. Research on generative AI in educational and professional settings further reinforces this interpretation. Studies consistently show that passive engagement with AI outputs—such as copying, accepting, or minimally editing generated content—is associated with shallow processing, reduced cognitive effort, and uncritical acceptance of plausible but flawed information (Ji et al., 2023; Kasneci et al., 2023). In contrast, when AI use is embedded within reflective and metacognitively demanding practices—including self-explanation, justification prompts, comparison of alternatives, or iterative critique—reasoning quality improves substantially (Kerrigan & Azevedo, 2022; Xie et al., 2024). Learners and practitioners in these conditions demonstrate greater awareness of uncertainty, stronger argumentation, and improved ability to detect errors or inconsistencies. Taken together, these findings indicate that AI itself is neither inherently beneficial nor inherently detrimental to human cognition. Rather, its cognitive impact is conditional, shaped by how individuals regulate their interaction with machine-generated outputs. AI can function as a powerful cognitive scaffold when it is used within a metacognitively regulated framework that encourages reflection, evaluation, and strategic control. Conversely, AI can function as a cognitive substitute when such regulation is absent, leading to cognitive offloading, automation bias, and diminished epistemic vigilance. Synthesised across these literatures, a central explanatory insight emerges: secondary thinking governs whether AI functions as a cognitive scaffold or as a cognitive substitute. When secondary thinking is active, individuals monitor both their own reasoning and the AI’s contributions, calibrate trust appropriately, and engage critical thinking when warranted. Under these conditions, AI supports exploration, comparison, and epistemic reflection. When secondary thinking is inactive or suppressed, AI reduces epistemic friction, obscures uncertainty, and encourages uncritical acceptance, thereby suppressing reasoning rather than enhancing it. This mediating role of secondary thinking provides the missing theoretical bridge linking metacognition research, critical thinking theory, and human–AI interaction studies. It explains why similar AI tools can produce radically different cognitive outcomes across users and contexts, and why interventions focused solely on improving AI accuracy or transparency are insufficient. Without attention to the metacognitive processes that regulate human–AI interaction, critical thinking cannot reliably fulfil its epistemic function within hybrid cognitive systems. By positioning secondary thinking as a mediator rather than a peripheral skill, this synthesis reframes human–AI reasoning as a metacognitively governed system. This reframing sets the foundation for the Human–AI Metacognitive Mediation (HAMM) model developed in the following section, which formalises these relationships and articulates their implications for education, leadership, and AI literacy. 6. The Human–AI Metacognitive Mediation (HAMM) Model 6.1 Conceptual Architecture Building on the preceding synthesis, the Human–AI Metacognitive Mediation (HAMM) model is proposed as an integrative theoretical framework for understanding reasoning in AI-mediated environments. The model is designed to explain how and why interactions between human cognition and machine-generated outputs produce variable epistemic outcomes, ranging from enhanced reasoning and learning to automation bias and cognitive offloading. Rather than conceptualising reasoning as a linear sequence in which human input is followed by machine output and then acceptance or rejection, the HAMM model frames human–AI reasoning as a dynamic, recursive system governed by metacognitive oversight. At the core of the HAMM model is the claim that reasoning quality in AI-mediated contexts is not determined solely by the accuracy of AI systems or the critical thinking ability of users. Instead, it is shaped by the regulatory processes that govern how human cognition and machine-generated contributions are integrated, monitored, and revised over time. Secondary thinking functions as the supervisory mechanism that coordinates this integration, ensuring that reasoning remains adaptive, context-sensitive, and epistemically responsible. The model comprises three interacting layers, each of which plays a distinct but interdependent role in hybrid reasoning: Layer 1: Primary Cognitive Inputs The first layer consists of primary cognitive inputs, which include fast, automatic human processes—such as heuristics, intuitions, emotional responses, and prior beliefs—as well as machine-generated outputs produced through probabilistic inference and pattern recognition. These inputs are characterised by speed and efficiency, allowing rapid generation of ideas, interpretations, and responses. However, they are also epistemically opaque, offering little intrinsic assurance of reliability or justification (Kahneman, 2011; Bender & Koller, 2020). In human cognition, primary processes are adaptive but vulnerable to bias and overconfidence. In machine cognition, outputs are fluent and scalable but indifferent to truth, meaning, or epistemic commitment. The HAMM model treats both sources symmetrically at this level: they provide raw material for reasoning, not warranted conclusions. Importantly, the model highlights that AI-generated content enters the reasoning process at the same level as intuitive human judgments, making regulatory oversight essential. Layer 2: Critical Thinking Processes The second layer comprises critical thinking processes, involving deliberate evaluation of claims, evidence, assumptions, and alternatives (Facione, 1990; Ennis, 2016). At this level, individuals assess coherence, consistency, relevance, and justification, including those associated with AI-generated outputs. Critical thinking enables comparison of alternatives, detection of inconsistencies, and evaluation of evidentiary support. Crucially, the HAMM model explicitly rejects the assumption that critical thinking is continuously active. Instead, it is treated as a conditionally deployed cognitive resource. Activation depends on perceived uncertainty, task demands, epistemic risk, and—most importantly—metacognitive signals originating from the supervisory layer. Without such activation, primary inputs may pass directly to judgment without scrutiny, regardless of their origin. Layer 3: Secondary Thinking (Metacognitive Mediation) The third layer consists of secondary thinking, conceptualised as metacognitive mediation. This supervisory layer performs three central regulatory functions: monitoring, control, and reflection. It monitors uncertainty, coherence, and conflict between human judgments and AI-generated suggestions; it controls reliance strategies by deciding when to defer to AI, when to override it, and when to seek alternative sources; and it supports reflection on epistemic assumptions, biases, and prior outcomes (Flavell, 1979; Efklides, 2008). Secondary thinking determines when critical thinking is activated, how intensively it is applied, and whether reliance on AI should be increased, reduced, or suspended. It thus functions as the gatekeeper of analytical engagement, ensuring that critical thinking is deployed where it is epistemically warranted rather than indiscriminately or not at all. A defining feature of the HAMM model is the recursive interaction among these layers. Outputs from critical thinking feed back into secondary thinking, updating trust calibration, confidence judgments, and future reliance strategies. Over time, this recursive process supports learning, adaptation, and the development of AI-specific metacognitive skills, allowing users to become more discerning and reflective participants in hybrid reasoning systems. 6.2 Theoretical Propositions From the conceptual architecture of the HAMM model, several theoretically grounded propositions follow. These propositions articulate testable relationships that link metacognitive regulation, AI use, and epistemic outcomes: a. Secondary thinking positively predicts calibrated trust in AI systems.Individuals with stronger metacognitive monitoring and control are better able to align their confidence in AI outputs with the system's actual reliability, thereby avoiding both over- and under-reliance. b. Trust calibration mediates the relationship between AI use and reasoning quality. AI use enhances reasoning outcomes only when trust is appropriately calibrated; miscalibration leads either to automation bias or to the rejection of valuable cognitive support. c. High AI fluency combined with weak secondary thinking increases susceptibility to automation bias.Fluent, confident AI outputs suppress analytical engagement when metacognitive oversight is weak, particularly under conditions of cognitive load or time pressure. d. Metacognitive scaffolds enhance epistemic outcomes in generative-AI tasks. Design features such as reflective prompts, uncertainty visualisations, self-explanation routines, and justification requirements activate secondary thinking and improve reasoning quality, transfer, and epistemic accountability (Azevedo et al., 2010; Xie et al., 2024). Together, these propositions position secondary thinking as the central explanatory variable linking machine cognition to human judgment and epistemic outcomes. They provide a theoretically coherent basis for empirical testing and for the design of educational, professional, and organisational interventions aimed at improving human–AI reasoning. 7. Implications for Education, Leadership, and AI Literacy 7.1 Doctoral and Higher Education Doctoral and advanced higher education constitute high-stakes epistemic environments in which originality, rigour, transparency, and accountability are central to scholarly legitimacy. Doctoral candidates are expected not only to produce novel contributions to knowledge, but also to demonstrate mastery over reasoning processes, evidentiary standards, and epistemic justification. In this context, the increasing reliance on generative AI for activities such as literature exploration, conceptual framing, methodological planning, data analysis, and academic writing introduces profound opportunities alongside equally significant risks. Empirical studies indicate that unregulated use of generative AI can result in hallucinated or fabricated citations, superficial synthesis of literature, erosion of argumentative coherence, and diminished engagement with primary sources (Ji et al., 2023; Kasneci et al., 2023). These risks are not merely technical or procedural; they are fundamentally epistemic. When AI-generated content is incorporated without reflective scrutiny, the integrity of scholarly reasoning is compromised, even when surface-level outputs appear coherent or sophisticated. The HAMM model reframes AI use in doctoral education not as a productivity shortcut to be managed through prohibition or detection, but as an object of metacognitive scrutiny. From this perspective, the core educational challenge is not whether doctoral candidates use AI, but how they regulate its influence on their reasoning processes. Secondary thinking becomes a central scholarly competence, enabling candidates to monitor how AI-generated suggestions shape their conceptual decisions, argumentative structure, and interpretation of evidence. Practically, this implies that doctoral education should incorporate explicit metacognitive practices related to AI use. These may include reflective AI-use logs, structured justification of AI-assisted decisions, and critical annotation of AI-generated outputs. Supervisory practices can also be adapted to foreground reasoning transparency, asking candidates not only what conclusions they reached, but how AI tools influenced the path to those conclusions. In this way, AI becomes a catalyst for deeper epistemic reflection rather than a threat to scholarly rigour. 7.2 Leadership and Strategic Decision-Making In leadership and executive contexts, AI systems are increasingly deployed for forecasting, risk modelling, scenario planning, policy analysis, and strategic decision-making. These applications place AI at the core of organisational judgment, often under conditions of uncertainty, time pressure, and high consequence. While AI promises enhanced analytical capacity and efficiency, it also amplifies well-documented cognitive vulnerabilities, particularly automation bias, when outputs align with intuitive judgments or reduce perceived cognitive effort (Green & Chen, 2019; Raisch & Krakowski, 2021). Leaders are especially susceptible to these dynamics because strategic decisions often involve ambiguous data, competing priorities, and limited feedback loops. Fluent AI-generated recommendations can create an illusion of certainty or objectivity, leading leaders to overestimate the reliability of algorithmic outputs or to defer judgment prematurely. In such contexts, failures are rarely attributable to lack of intelligence or experience. Instead, they reflect insufficient regulation of how machine-generated insights are interpreted and integrated into human judgment. The HAMM model positions secondary thinking as a core leadership capability. Effective leaders must be able to step back from AI outputs, interrogate underlying assumptions, recognise model limitations, and reflect on how cognitive biases—both human and algorithmic—shape decision outcomes. Secondary thinking supports epistemic humility by reminding leaders that AI systems are probabilistic, context-dependent, and value-laden rather than neutral arbiters of truth (Floridi, 2019; Gigerenzer, 2020). Leadership development programmes should therefore move beyond instrumental AI training and incorporate metacognitive components. AI-augmented decision simulations, followed by structured debriefs focused on reasoning processes rather than outcomes alone, can help leaders develop awareness of trust calibration, over-reliance, and cognitive offloading. Such practices align strategic competence with epistemic responsibility, ensuring that AI enhances rather than displaces human judgment. 7.3 AI Literacy Frameworks Current AI literacy frameworks typically emphasise technical understanding, ethical awareness, and the ability to critically evaluate AI outputs (Long & Magerko, 2020). While these dimensions are essential, they often underemphasise the metacognitive regulation of human–AI interaction. As a result, AI literacy is frequently framed as knowledge about AI rather than competence in managing how AI reshapes one’s own thinking. The HAMM model extends existing AI literacy frameworks by positioning secondary thinking as a foundational literacy component. From this perspective, AI literacy involves not only understanding what AI systems can and cannot do, but also recognising how interaction with AI alters cognitive effort, attention allocation, confidence judgments, and epistemic vigilance. Literate users are those who can monitor their reliance on AI, detect when critical thinking is being suppressed, and deliberately re-engage analytical scrutiny when warranted. Embedding secondary thinking into AI literacy initiatives has implications across educational and professional domains. Curricula should incorporate reflective prompts, uncertainty interrogation, and explicit discussion of cognitive offloading and automation bias. Rather than focusing solely on correct use of tools, AI literacy should cultivate awareness of how reasoning itself changes in AI-mediated environments. By foregrounding metacognitive regulation, the HAMM model reframes AI literacy as a form of cognitive self-governance. This reframing aligns AI education with broader goals of epistemic agency, responsible judgment, and human flourishing in technologically mediated societies. 8. Conclusion This article demonstrates that the central cognitive challenge of the AI era is not a deficit of critical thinking, but a deficit of effective metacognitive regulation in hybrid human–AI reasoning systems. By integrating metacognition theory, critical thinking research, and human–AI interaction studies, it shows that secondary thinking mediates the epistemic impact of machine cognition. The HAMM model provides a theoretically grounded explanation for automation bias, cognitive offloading, and trust miscalibration, while offering actionable implications for education, leadership, and AI literacy. As AI systems become increasingly embedded in cognitive and societal processes, human agency will depend not only on what we think, but on our capacity to think about how we think with machines. References Azevedo, R., Moos, D.C., Johnson, A.M. and Chauncey, A.D. 2010. 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It is founded for the purpose of supporting and further deepening multi-party democracy. The ISI’s work is motivated by its desire to achieve non-racialism, non-sexism, social justice and cohesion, economic development and equality in South Africa, through a value system that embodies the social and national democratic principles associated with a developmental state. It recognises that a well-functioning democracy requires well-functioning political formations that are suitably equipped and capacitated. It further acknowledges that South Africa is inextricably linked to the ever transforming and interdependent global world, which necessitates international and multilateral cooperation. As such, the ISI also seeks to achieve its ideals at a global level through cooperation with like-minded parties and organs of civil society who share its basic values. In South Africa, ISI’s ideological positioning is aligned with that of the current ruling party and others in broader society with similar ideals. Email: info@inclusivesociety.org.za Phone: +27 (0) 21 201 1589 Web: www.inclusivesociety.org.za

Read the full journal, including this article, by downloading the PDF below. Image credit: AI-generated illustration produced with OpenAI (DALL·E), 2026. by Daryl Swanepoel Abstract South Africa’s National Health Insurance (NHI) reform represents a major institutional restructuring aimed at achieving universal access to quality healthcare. While the principle of universal coverage is constitutionally grounded and widely supported, debate centres on system design, fiscal sustainability and governance resilience. At the time of writing, the NHI Act is subject to Constitutional Court scrutiny, with challenges focusing on financing feasibility, governance concentration and the restriction of private medical schemes. In this context, comparative analysis is instructive. This paper examines China’s national health insurance architecture as a reference point. Over three decades, China has expanded basic medical insurance coverage to approximately 95% of its population through a layered, contributory and fiscally bounded system. Rather than relying on a single exclusive fund, China operates multiple core insurance schemes supplemented by municipal add-ons and commercial private cover. Benefits are defined, contributions are structured and cost control mechanisms, including Diagnosis-Related Group payment models and volume-based procurement, are embedded in the financing framework. While China’s political system differs markedly from South Africa’s, its institutional design choices highlight key principles: layered risk pooling, bounded benefits, contribution discipline and sequencing clarity. Universal coverage, the paper argues, is ultimately an institutional design challenge requiring fiscal realism alongside social solidarity. Keywords: National Health Insurance (NHI), Universal Health Coverage, China Healthcare System, Healthcare Financing, Institutional Design Introduction: Why study China now? South Africa stands at a pivotal moment in the reform of its healthcare system. The National Health Insurance (NHI) Act has been signed into law, and the country now faces the practical question of how such a system is to be structured, financed and implemented. The aspiration underlying the Act, universal access to affordable, quality healthcare, is not controversial in principle; instead, it is grounded in constitutional commitment (RSA, 1996) and in a broadly shared moral conviction that healthcare should not be determined by income alone. The debate in South Africa is therefore not fundamentally about whether universal health coverage is desirable. It is about design. It is about sequencing. It is about institutional resilience. Several structural concerns have crystallised in public debate and in legal challenges currently before the Constitutional Court. The proposal to concentrate healthcare purchasing authority in a single national fund has raised questions of systemic concentration risk. Critics ask whether placing the entirety of national health financing under one institutional roof introduces vulnerability in the event of governance failure, fiscal miscalculation or administrative incapacity, and in a country that has witnessed the fragility of concentrated public monopolies in other sectors, this concern resonates widely (Stokes, 2026; Jeffery, n.d.). A second issue relates to the Act’s restriction of private medical schemes to mere complementary cover. South Africa presently operates a dual system in which private medical aids and private hospitals function alongside a tax-funded public health sector, but the envisaged NHI framework signals a shift toward exclusivity, by limiting the role of private schemes in areas covered by the national fund. The implications of such limitation for investment, choice, specialist retention and system resilience remain intensely debated (Jeffery, n.d.). Thirdly, the governance architecture has come under scrutiny, in that the concentration of appointment and oversight powers within the executive has raised questions about whether there are sufficient checks and balances, and it is further argued that the durability of any large-scale social insurance system cannot depend only on actuarial soundness, but also on the system’s institutional credibility across political cycles (Jeffery, n.d.). These structural concerns are compounded by the absence of a consolidated, costed financing white paper that details revenue instruments, contribution rates, transitional costs, and the long-term actuarial modelling that will be applied (Stokes, 2026). During prior consultations between the Inclusive Society Institute and the Department of Health, it was suggested that implementation may proceed incrementally “as finances permit” (Swanepoel, 2026). While phasing is common in major reform, open-ended finance-contingent rollout introduces sequencing risk. Universal insurance reform restructures institutional arrangements in ways that are not easily reversible. It is important to note that South Africa does not approach universal healthcare from a position of absence. A large proportion of the population already enjoys access to public healthcare services that are free at the point of use (Baugh, n.d.). In this respect, there are superficial similarities with earlier models of low-cost or state-supported access observed in other systems. However, international experience suggests that the sustainability of such arrangements depends not on access provisions alone, but also on the alignment between funding, institutional capacity and provider incentives. Where this alignment is weak, access may remain formally available, but system performance deteriorates. This aligns with a broader body of health systems literature that emphasises that universal coverage outcomes depend largely on the coherence between the financing arrangements underpinning the system, as well as the incentives given to providers and the capacity of the institutions (World Bank, 2016; Yip et al., 2019). The central challenge is therefore not only to expand access to healthcare, but also to ensure that the underlying arrangements are capable of sustaining the system (Leng, 2026). Financing clarity, therefore, is not peripheral; it is foundational. A further dimension, insufficiently developed in current debates, concerns the relationship between insurance design and the underlying economics of healthcare provision. International experience suggests that large-scale insurance reforms cannot be assessed in isolation from hospital financing models, service pricing structures and provider remuneration systems. Where these elements are misaligned, systemic pressures may emerge irrespective of the formal design of the insurance mechanism itself. In the South African context, limited clarity has thus far been provided on how public hospital funding, tariff setting and practitioner incentives will evolve alongside the implementation of the NHI. Without parallel reform in these areas, the risk arises that financial strain and incentive distortions may undermine system performance, even if the insurance architecture is conceptually sound. It is within this context that the Inclusive Society Institute has embarked on a series of comparative country studies. This China study (Beijing Dialogue) constitutes the first in a structured series of country analyses, to be followed by field studies of Finland and Thailand, before a consolidated comparative synthesis is produced. The purpose is not to advocate transplantation. South Africa’s constitutional, fiscal and administrative environment is unique. Rather, the purpose is diagnostic: to examine how countries with different political systems and developmental trajectories have structured universal coverage, managed financing risk, and navigated the relationship between public and private provision. China offers a particularly instructive case. It is neither a small welfare state, nor a conventional liberal democracy; it is a vast and administratively complex polity that has expanded health insurance coverage to approximately 95% of its population over the past three decades (PRC, 2024). Its governance model differs profoundly from that of South Africa, but it has confronted challenges common to all systems pursuing universal coverage: fiscal sustainability, cost control, rural inclusion, hospital reform and the role of private finance. The Chinese experience is therefore examined here as a reference point. It allows us to explore how universal coverage can be structured at scale, what financing disciplines underpin it, and how layered insurance mechanisms function within a national framework. Historical evolution: From state provision to contributory insurance China’s contemporary health insurance system did not emerge fully formed; instead, it evolved. Prior to the mid-1990s, healthcare provision was largely state funded within a centrally planned economy. However, as market reforms deepened in China, the limitations of a purely budget-funded healthcare system became apparent; and in the wake of rising costs, demographic shifts and economic liberalisation, the necessary pressure was created to move towards a more structured insurance model that was capable of funding the healthcare system within the changing environment (Swanepoel, 2026). The reform process is commonly associated with a number of critical milestones, the first of which began in 1989, when China initiated pilot reforms of the medical insurance system. Contributory model pilots were introduced in 1994, followed by the formal establishment of the Basic Medical Insurance system for Urban Employees in 1998. In 2003, rural cooperative medical schemes were expanded significantly in order to address the gaps in coverage of those who found themselves outside the formal urban workforce. And in 2007, the Urban Resident Basic Medical Insurance scheme was introduced, which scheme extended coverage to non-employed urban populations, thereby closing a critical gap in the emerging system. By 2008, coverage had expanded rapidly across both urban and rural populations, extending access across both geographic and income divides, with institutional integration between urban and rural resident schemes formally achieved through the 2016 reform (Leng, 2026; Swanepoel, 2026). Subsequent reforms consolidated fund administration under the National Healthcare Security Administration, which strengthened cost-control mechanisms that international observers have described as being incremental but expansive, given that it combined rapid coverage growth with evolving institutional reform (World Bank, 2016; Yip et al., 2019). What is notable about this historical arc is not simply the speed of expansion, but also the consistent embedding of financing parameters at each stage, with reform phases not framed as open-ended entitlement expansions. They were accompanied by defined contribution structures, reimbursement rules and cost-management mechanisms. Architecture of coverage: A layered system, rather than a monolith China’s health insurance system is often colloquially described as “national”. Yet the Beijing consultations revealed a more nuanced architecture. The system operates across multiple layers. At its foundation are two principal social insurance schemes. The Urban Employee Basic Medical Insurance covers formally employed workers. Contributions are salary-linked, with employees contributing approximately 2% of their income and employers contributing a significantly larger amount, typically between 6% and 8%. The payroll-based structure anchors the system in contributory discipline (Swanepoel, 2026). The Urban and Rural Resident Basic Medical Insurance also covers individuals who work outside of formal employment. These participants contribute an annual premium commonly reported at several hundred renminbi, while central and local governments provide substantial subsidies (Swanepoel, 2026). Vulnerable groups, including the elderly and low-income citizens, may have their premiums fully subsidised by government programmes (Swanepoel, 2026). These two schemes form the core layer, covering the vast majority of the population, but coverage under these schemes is not unlimited, and reimbursement levels vary according to the level of hospital and the nature of care. Primary facilities may see high reimbursement ratios, whereas tertiary hospitals, which provide specialised and advanced services, often reimburse approximately half to sixty percent of costs, with the remainder covered by the individual or supplementary insurance (Swanepoel, 2026). Above this foundational layer sit supplementary mechanisms such as municipal insurance products like “Huimin Bao”, which offers inexpensive add-on coverage designed to absorb the costs attached to catastrophic or high-cost treatments that are not fully covered under the core scheme. In addition, critical illness insurance cover and emerging long-term care insurance products further extend protection against specific risk categories (Swanepoel, 2026). Finally, fully commercial private insurance products operate alongside the public system, and these products typically cover innovative therapies, advanced pharmaceuticals, enhanced service options and VIP facilities. Furthermore, it is important to note that private insurance is not prohibited and that it functions as a complement to the public scheme (Swanepoel, 2026). The overall structure of the health system is therefore layered, rather than monolithic, whereby universal coverage exists within a framework that accommodates both supplementary and private financing. Financing discipline: Contributions, co-payments and cost controls Three features of the Chinese system stand out in financing terms: contribution discipline, bounded benefits and active cost control. First, the system is contributory. Even residents outside formal employment contribute defined premiums, albeit subsidised. The principle that beneficiaries contribute something toward the system, either directly or through payroll, is embedded structurally (Swanepoel, 2026). This contribution culture mitigates the perception of unlimited entitlement. Second, benefits are bounded. China operates defined reimbursement lists for medicines and treatments, meaning that only items included on approved lists are reimbursed through the social insurance scheme. Therapies outside the list may require out-of-pocket payment or private insurance. The benefit package is therefore best described as being circumscribed, rather than being open-ended (Swanepoel, 2026). Third, cost control mechanisms are integral to the system, where the Diagnosis Related Group (DRG) payment models increasingly govern hospital reimbursement, by establishing fixed payments per case. Hospitals that deliver care below the benchmark retain efficiencies; those exceeding the benchmark share in losses. In this manner, incentives are shifted away from pure fee-for-service escalation (Swanepoel, 2026). Volume-based pharmaceutical procurement is another key mechanism, best illustrated through the leveraging of its national purchasing power, where authorities negotiate bulk agreements with drug manufacturers, which has resulted in significant price reductions in many categories (Swanepoel, 2026). This strategic purchasing reflects an understanding that universal coverage must be accompanied by aggressive expenditure management, and together, these mechanisms suggest a coherent fiscal philosophy, which is that solidarity must operate within financial constraints. While these features of the insurance architecture are central to the system’s performance, they do not operate in isolation. The evolution of China’s medical insurance system has been closely intertwined with broader reforms in hospital financing, service pricing and provider remuneration. Under earlier reform phases, public hospitals were permitted to rely on drug mark-ups to sustain operations, but this particular mechanism was later removed as part of cost-control efforts. However, the removal of the drug mark-up mechanism required compensating adjustments in other areas, including increased government funding, the recalibration of medical service prices and reforms to physician remuneration structures; and when such adjustments did not keep pace, financial pressures on hospitals and distortions in provider incentives emerged. This illustrates that the sustainability of the insurance system is not only contingent on its internal design, but equally so on its alignment with the wider political economy of healthcare provision (Leng, 2026). Governance structure: Administrative separation within Executive Authority The governance of the Chinese healthcare system is administratively structured, with the National Health Commission overseeing the healthcare delivery standards and regulatory matters, and the National Healthcare Security Administration managing insurance financing and the funding of operations. Pharmaceutical regulation, in turn, falls under separate administrative authority (Swanepoel, 2026). Appointments are executive in character, reflecting China’s governance model. Oversight ultimately flows through governmental reporting structures, rather than through parliamentary separation as found in liberal democracies. Yet, functional separation between service regulation and fund administration exists. The insurance authority focuses on financing, reimbursement and cost control, while health commissions oversee clinical standards and institutional performance (Swanepoel, 2026). This administrative segmentation does not mirror South Africa’s constitutional framework. Nonetheless, it demonstrates that large-scale national insurance systems may divide operational functions, even within centralised governance models. Public and private provision: Coexistence and accreditation China’s hospital landscape is dominated by public institutions, particularly the tertiary academic hospitals, which carry the majority of complex caseloads. But that said, private hospitals exist in substantial numbers, and they often focus on specialised or elective services (Swanepoel, 2026). Doctors employed in public hospitals may also practise part time in private facilities if they so wish. Accredited private hospitals may accept social insurance reimbursement, provided they meet prescribed standards. Facilities that fail to meet standards may not access public insurance reimbursement; they are, however, allowed to continue operating, provided they are properly licensed (Swanepoel, 2026). Importantly, this coexistence is not limited to complementary or innovative services only; accredited private hospitals may provide procedures that are included in the public reimbursement list. Moreover, social insurance covering the eligible portion of the cost may be claimed, with patients settling the remaining co-payment through out-of-pocket expenditure or supplementary insurance. Private insurance may in turn cover the portion of the co-payment already included in the public scheme, as well as the additional financing required to fund enhanced service levels. This therefore suggests that the relationship between public and private financing is one that overlaps, rather than being mutually exclusive (Swanepoel, 2026). This accreditation mechanism reinforces quality oversight while permitting ownership diversity. The insurance fund contracts with all providers are based on standards, regardless of ownership form. Regional variation and local fund capacity Although described as national, China’s system exhibits regional variation, in that reimbursement ratios may differ across cities depending on local fund capacity; wealthier regions may sustain higher reimbursement levels, whereas less affluent regions may impose greater cost sharing (Swanepoel, 2026). This partial decentralisation reflects fiscal realities within a large and diverse country, and it also introduces an element of distributed risk, as financing is not entirely homogenised across all regions. Implementation and sequencing China’s universal coverage did not emerge through abrupt structural overhaul. Instead, reform phases were incremental, but defined, with each expansion stage accompanied by the introduction of specified contribution rates and reimbursement parameters (Swanepoel, 2026). The sequencing appears deliberate in that the financing architecture was articulated alongside expansion in coverage, meaning that reform did not proceed on an open-ended “as finances permit” basis; instead, it was embedded within clearly defined fiscal parameters (Swanepoel, 2026). International assessments emphasise that while challenges remain, China has combined coverage expansion with continuous cost management and institutional strengthening (Yip et al., 2019). Strengths and tensions within the model The Chinese model’s strengths include near-universal coverage, defined contribution structures, layered financing and embedded cost control mechanisms. The coexistence of private insurance and public coverage introduces risk buffering and service diversity. However, tensions between the private and public systems remain, regional disparities in reimbursement persist, and the integration of health records and insurance databases continues to evolve. Public hospitals dominate specialised care, potentially limiting competitive dynamics, and governance remains executive-centric. Yet the structural logic is coherent: universal coverage is pursued within contributory discipline and bounded fiscal commitment. Analytical reflections The Chinese experience illustrates several broader design principles. Universal coverage does not require elimination of supplementary or private insurance. Layered risk pooling can coexist with solidarity. Cost control must be systemic, rather than reactive, and therefore DRGs, procurement negotiation and reimbursement lists are not peripheral features; they are, indeed, foundational. Contribution discipline reinforces sustainability. Even modest premiums create a participatory financing culture. Sequencing matters, and as such, financing parameters tend to accompany expansion rather than follow it. These observations do not imply transplantation, but instead they provide comparative insight. In evaluating any national insurance reform, key questions arise, namely: How is risk distributed? How is concentration mitigated? How are incentives structured? How is financing defined before structural consolidation proceeds? China’s system reflects one coherent set of answers. It demonstrates that universalism and plurality need not be in tension. It shows that solidarity can operate within layered financing. It confirms that cost discipline is inseparable from coverage ambition. Comparative reflections: Institutional design and ongoing legal scrutiny The relevance of the Chinese experience does not lie in its political structure, nor in the scale of its economy, but in the institutional design questions it surfaces, and when placed alongside South Africa’s current reform trajectory, certain analytical observations emerge. At the time of writing this report, the National Health Insurance Act is under judicial review in the Constitutional Court of South Africa. Cases have been brought challenging the rationality of the President’s decision to assent to the Act, and questions are being raised about the National Insurance Fund’s governance design, its financing feasibility and its constitutional compliance (Business Day, 2026). The litigation also raises questions relating to the Fund’s governance structure, the concentration of financial authority, the restriction of private medical schemes, and the broader rationality and feasibility of the financing model. These Constitutional Court proceedings form part of the wider policy context within which universal healthcare reform is being assessed in South Africa. Against this backdrop, the Chinese case does not necessarily offer South Africa a template that can be duplicated wholesale, but it does serve to illuminate how another large and complex society has navigated similar structural questions to those confronting the country. One of the central issues in South Africa concerns the concentration of purchasing authority within a single national fund. China's system, while nationally coordinated, operates through layered mechanisms, whereby the core social insurance schemes are complemented by supplementary municipal insurance products and fully commercial private cover; reimbursement ratios, in turn, vary across regions, thereby reflecting local fund capacity. In effect, risk is not absorbed through a singular exclusive channel but distributed across a structured set of financing tiers, and while this does not eliminate fiscal pressure, it does create buffers. A second concern in South Africa relates to the restriction of private medical schemes to complementary services. In China, private insurance was not dismantled during the expansion of universal coverage; on the contrary, supplementary and commercial insurance products play a defined role, particularly in covering innovative therapies and higher service levels. Universalism, in this context, did not require exclusivity. It required delineation. Governance architecture also differs markedly. China’s appointments are executive in character, reflecting its political structure. Yet operational responsibilities are institutionally divided between healthcare regulation and insurance fund administration. Functional segmentation exists even within centralised governance. While South Africa’s constitutional framework is distinct, the broader principle that financing administration and healthcare oversight may be separated is evident. Perhaps most significant for present purposes is the question of sequencing. China’s reform phases were accompanied by defined contribution structures, reimbursement parameters and cost-control mechanisms. Coverage expansion was embedded within articulated financing architecture. Reform did not proceed on an undefined “as finances permit” basis; rather, fiscal parameters were clarified alongside structural rollout. The implication is not that financing challenges disappear, but that clarity precedes consolidation. These observations do not resolve South Africa’s debate. They do, however, demonstrate that universal coverage elsewhere has been constructed through layered financing, bounded benefit packages and institutionalised cost discipline, rather than through singular institutional concentration. For South Africa, where universal access remains a legitimate national aspiration, the enduring design question is not whether coverage should expand, but how institutional resilience, fiscal clarity and risk distribution are embedded at the outset. Conclusion China’s national health insurance architecture is best understood not as a single centralised fund, but as a layered, contributory and bounded system that has evolved over three decades. Coverage is broad, but not unlimited. Private insurance remains operative. Cost control is institutionalised. Reform has been phased and parameter-defined. The model is embedded within China’s political and administrative context and cannot be transposed wholesale. Yet its structural features — layered financing, contribution discipline, defined reimbursement and coexistence with private provision — offer valuable comparative insights for any middle-income country contemplating large-scale health insurance reform. 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National Health Insurance study visit to China and dialogue with Chinese Health Sector experts. Beijing, 28 January 2026. World Bank. 2016. Deepening Health Reform in China. [Online] https://openknowledge.worldbank.org/server/api/core/bitstreams/ab618635-7f02-5459-bfd1-cee55d848960/content. [accessed: 19 February 2026]. Yip, W. et al. 2019. 10 years of health-care reform in China: progress and gaps in Universal Health Coverage, The Lancet, 394(10204), pp. 1192–1204. This report has been published by the Inclusive Society Institute The Inclusive Society Institute (ISI) is an autonomous and independent institution that functions independently from any other entity. It is founded for the purpose of supporting and further deepening multi-party democracy. The ISI’s work is motivated by its desire to achieve non-racialism, non-sexism, social justice and cohesion, economic development and equality in South Africa, through a value system that embodies the social and national democratic principles associated with a developmental state. It recognises that a well-functioning democracy requires well-functioning political formations that are suitably equipped and capacitated. It further acknowledges that South Africa is inextricably linked to the ever transforming and interdependent global world, which necessitates international and multilateral cooperation. As such, the ISI also seeks to achieve its ideals at a global level through cooperation with like-minded parties and organs of civil society who share its basic values. In South Africa, ISI’s ideological positioning is aligned with that of the current ruling party and others in broader society with similar ideals. Email: info@inclusivesociety.org.za Phone: +27 (0) 21 201 1589 Web: www.inclusivesociety.org.za

Read the full journal, including this article, by downloading the PDF below. Image credit: AI-generated illustration produced with OpenAI (DALL·E), 2026. by Sameh Abidi Abstract The introduction of theCarbon Border Adjustment Mechanism (CBAM) by the European Union represents a structural transformation at the intersection of climate policy and international trade. Designed to prevent carbon leakage and ensure a level playing field between European producers subject to the EU Emissions Trading System (ETS) and foreign exporters, the mechanism applies a carbon price to selected imported goods such as cement, fertilizers, aluminium, and electricity. While CBAM reinforces the credibility of European climate ambition under the Paris Agreement, it also generates significant economic challenges for neighbouring economies closely integrated into European value chains. This paper examines the implications of CBAM for Tunisia, where approximately 70% of exports are directed toward the European market and where industrial production remains both carbon-intensive and highly dependent on fossil fuels. By focusing on the sectors most exposed to the mechanism—cement, fertilizers, aluminium, and electricity—the study provides a quantitative-informed assessment of potential impacts. Preliminary estimates suggest that carbon pricing levels ranging between €70 and €95 per ton of CO₂ (https://sl1nk.com/vcOIq) could substantially increase export costs in energy-intensive sectors, potentially reducing profit margins and undermining international competitiveness. At the macroeconomic level, these effects may translate into indirect fiscal pressures through declining export revenues, lower industrial output, and increased demands for public investment in energy transition. In this context, CBAM operates as an implicit carbon tax on Tunisia’s energy system, revealing structural vulnerabilities in the country’s industrial model. However, beyond these immediate risks, the mechanism may also act as a catalyst for structural transformation. The transition toward green industrialisation is no longer solely an environmental objective but an economic necessity for maintaining access to European markets. The development of renewable energy, particularly solar and wind power, combined with improvements in industrial energy efficiency and thedecarbonisation of energy-intensive sectors, could enable Tunisia to reposition itself within emerging Euro–Mediterranean green value chains. The paper further examines the fiscal and financial implications of this transition. Tunisia faces constrained public finances and rising debt levels, limiting its capacity to finance large-scale decarbonisation investments. European financial instruments, including the Global Gateway initiative and financing from the European Investment Bank (EIB) and the European Bank for Reconstruction and Development (EBRD), are analysed as potential sources of support. However, their predominantly loan-based structure and associated conditionalities raise concerns regarding debt sustainability and long-term fiscal stability, particularly in the absence of sufficient grant-based financing. In addition, the study integrates the social dimension of the transition by highlighting potential risks related to employment in carbon-intensive sectors, regional inequalities, and unequal access to green investment opportunities. Without adequate mitigation measures, the decarbonisation process could exacerbate existing socio-economic disparities. Against this backdrop, the article raises a central question: Can the European Union impose a carbon cost on imports without providing proportional financial and technological support to its trading partners? Addressing this issue requires incorporating principles of climate justice, including differentiated responsibilities and equitable burden sharing in the global energy transition. Without such considerations, CBAM risks reinforcing existing asymmetries in international trade and development. To transform CBAM into a lever for co-development rather than a punitive trade instrument, the paper proposes a set of operational and sector-specific policy recommendations. These include allocating a share of CBAM revenues to partner countries, increasing the use of grants in European climate finance, promoting targeted industrial decarbonisation strategies, and strengthening technological cooperation between European and Tunisian industries. At the national level, priorities include securing domestic energy supply, ensuring local industrial participation in green investments, safeguarding fiscal sustainability, and enhancing transparency in international partnerships. Finally, the paper emphasises the importance of inclusive governance mechanisms that integrate civil society participation and parliamentary oversight in the design and implementation of climate-related economic policies. A transition financed primarily through external debt risks undermining the very development objectives it seeks to achieve. Ultimately, the success of Tunisia’s transition will depend not only on financial and technological resources but also on institutional capacity, fiscal governance, and the ability to ensure a socially just and economically sustainable transformation. In conclusion, the Carbon Border Adjustment Mechanism represents a pivotal moment in the evolving relationship between climate governance, trade policy, and industrial development. For Tunisia, it may either deepen structural vulnerabilities or serve as a catalyst for a new model of sustainable industrialisation. The outcome will depend on the extent of alignment between European climate ambitions, Tunisian industrial strategies, and broader reforms toward a more equitable and inclusive global energy transition. Keywords: Carbon Border Adjustment Mechanism (CBAM), Green Industrialisation, Tunisia, Energy Transition, Euro-Mediterranean Green Value Chains Introduction Climate policies are increasingly shaping global trade and industrial development. In recent years, climate governance has expanded beyond environmental regulation to become a central element of international economic policy. One of the most significant developments in this area is the European Union’s Carbon Border Adjustment Mechanism (CBAM), introduced as part of the European Green Deal and the broader Fit for 55 legislative package, which aims to reduce greenhouse gas emissions by at least 55 percent by 2030 compared to 1990 levels (European Commission, 2023).(https://l1nq.com/m99Rl) The CBAM represents a structural shift in global climate governance. For the first time, a major economic bloc is integrating carbon pricing into international trade policy by applying a carbon cost to imported goods. This mechanism aims to prevent carbon leakage, a phenomenon in which industries relocate production to countries with weaker environmental regulations in order to avoid carbon pricing constraints (Zachmann, Roth & Tamara, 2020). While CBAM primarily seeks to protect the environmental integrity of European climate policies, its economic implications extend far beyond the EU. Countries exporting carbon-intensive products to the European market will increasingly face regulatory requirements related to emissions reporting and carbon pricing. For developing economies that rely heavily on industrial exports to the EU, these changes may significantly affect trade competitiveness (World Bank, 2023). Tunisia is particularly exposed to these developments due to its strong economic integration with European markets. The European Union represents Tunisia’s largest trading partner, accounting for approximately 70 percent of its exports (European Commission, 2023). Several Tunisian industrial sectors that export to Europe, including cement, fertilizers, and metal products, are energy-intensive and rely largely on fossil fuels, especially natural gas. As a result, the introduction of CBAM may increase export costs for Tunisian industries and potentially weaken their competitiveness in European markets. At the same time, the mechanism may act as a catalyst for industrial modernisation and energy transition. This article examines how Tunisia can transform the constraints imposed by CBAM into an opportunity for green industrialisation while maintaining fiscal sustainability and economic competitiveness. It argues that while CBAM functions as an indirect carbon tax on Tunisia’s industrial structure, it may also accelerate structural reforms toward a low-carbon industrial economy if accompanied by appropriate financial support, technology transfer, and policy coordination between Tunisia and the European Union. 1. CBAM: A New Industrial Challenge for Tunisia 1.1. Understanding the Carbon Border Adjustment Mechanism The Carbon Border Adjustment Mechanism (CBAM) is one of the flagship instruments of the European Green Deal. It was introduced to address a central challenge in global climate policy: ensuring that products imported into the European Union bear a carbon cost comparable to that faced by European producers. By doing so, the mechanism aims to preserve fair competition in the European market while supporting the EU’s broader climate objectives. CBAM was designed to complement the European Union’s Emissions Trading System (EU ETS), which represents the EU’s main policy tool for reducing greenhouse gas emissions (European Commission, 2023). Under the ETS framework, companies operating in certain sectors must purchase emission allowances corresponding to the amount of carbon dioxide emitted through their activities. These allowances create a market-based carbon price that incentivises industries to invest in cleaner technologies and reduce their emissions over time. However, differences in climate regulations across countries can create significant competitive distortions. European industries that are subject to carbon pricing may face higher production costs compared to foreign competitors operating in jurisdictions with weaker environmental regulations or without carbon pricing mechanisms. This situation may encourage companies to relocate production to countries where climate policies are less stringent, a phenomenon commonly referred to as carbon leakage. Such relocation risks undermining the EU’s climate efforts by shifting emissions abroad rather than reducing them globally. The CBAM seeks to address this challenge by extending the principle of carbon pricing to imports. Under this mechanism, importers of certain goods into the European Union are required to purchase CBAM certificates corresponding to the carbon emissions embedded in those products. The price of these certificates is linked to the weekly average price of emission allowances under the EU ETS, ensuring consistency between the carbon costs borne by European producers and those applied to imported products (World Bank, 2023). Through this approach, the EU aims to establish a level playing field between domestic and foreign producers. The implementation of the CBAM is taking place in phases. The transitional period (2023–2025) requires companies exporting to the EU to report the carbon emissions embedded in their products without yet paying a financial adjustment. This phase is intended to allow both exporting countries and EU authorities to develop robust monitoring, reporting, and verification systems. Starting in 2026, the financial component of the CBAM will become fully operational, requiring importers to purchase carbon certificates corresponding to the emissions embedded in imported goods (European Commission, 2023). Currently, the mechanism applies to several sectors that are both highly carbon-intensive and significantly exposed to international trade. These include cement, iron and steel, aluminium, fertilizers, electricity, and hydrogen (OECD, 2023). These industries were selected because they represent a large share of industrial emissions and are particularly vulnerable to carbon leakage. Beyond its regulatory dimension, the CBAM represents a strategic instrument for the global transition toward a low-carbon economy. For European companies, it protects the value of investments made in decarbonisation by preventing carbon-intensive imports from undermining their competitiveness. For exporters outside the EU, the mechanism presents both a challenge and an opportunity. Firms that anticipate these changes and adapt their production processes can transform compliance into a competitive advantage, improve their environmental reputation, and secure long-term access to one of the world’s most demanding markets in terms of sustainability. Ultimately, the CBAM goes beyond a simple trade or fiscal measure. It constitutes a key tool of climate governance that seeks to align international trade with climate objectives while encouraging a broader transformation toward low-carbon industrial production. Main Objectives and Operational Mechanisms of CBAM Main Objective Description / Operational Mechanism 1. Limiting Carbon Leakage Companies may relocate production to countries with weaker environmental regulations, undermining EU climate policies. The Carbon Border Adjustment Mechanism (CBAM) addresses this by ensuring that the carbon emissions embedded in imported goods are reflected in their price, thereby discouraging the relocation of production to jurisdictions with lower environmental standards. 2. Creating a Carbon Price Signal for Imports CBAM converts embedded emissions into an economic cost for imported goods. This creates an incentive for non-EU producers to reduce their greenhouse gas emissions in order to remain competitive in the EU market, thereby encouraging decarbonisation beyond the EU's borders. 3. Supporting the EU's 2050 Carbon Neutrality Goal CBAM supports the EU's long-term objective of achieving climate neutrality by 2050. It prevents imported goods from undermining the effectiveness of EU climate policies and complements other European Green Deal initiatives, including the EU Emissions Trading System (EU ETS), the European Climate Pact, and circular economy policies. 4. Emissions Reporting Importers are required to identify, quantify, and report the direct emissions (generated during production) and, where applicable, indirect emissions (associated with energy consumption) embedded in imported products. These reports must be accurate and supported by credible evidence, such as supplier declarations, verified emissions reports, or independent third-party audits. 5. Purchase of CBAM Certificates Importers must purchase CBAM certificates corresponding to the embedded CO₂ emissions of imported goods. The price of these certificates is linked to the prevailing EU ETS carbon price, ensuring that imported and domestically produced goods face equivalent carbon costs and creating a level playing field within the EU market. 1.2. Tunisian Industrial Sectors Exposed to CBAM Several Tunisian industries are directly or indirectly exposed to CBAM due to their energy intensity and export orientation. The cement sector is one of the most energy-intensive industries in Tunisia. Cement production requires high-temperature kilns fuelled by fossil fuels and involves chemical processes that release large quantities of carbon dioxide (IEA, 2023). If Tunisian cement producers export to European markets, they will face additional carbon costs under CBAM. The fertilizer industry represents another important sector. Tunisia is one of the world’s major producers of phosphate-based fertilizers. However, fertilizer production relies heavily on energy-intensive processes and fossil fuel inputs, increasing the carbon intensity of these products. The aluminium and metal-processing sectors may also face indirect exposure. Even if certain products are not directly covered, the carbon intensity of electricity used in production will affect overall competitiveness. Electricity exports could also become relevant in the future if Tunisia expands energy interconnections with European markets. In such a case, the carbon intensity of Tunisia’s electricity generation would determine its ability to compete with low-carbon European electricity. 1.3. Potential Economic Impacts The economic implications of CBAM for Tunisia are likely to be multifaceted. First, exporters will face increased compliance costs related to monitoring and reporting emissions. Establishing Monitoring, Reporting, and Verification (MRV) systems requires institutional capacity, technical expertise, and investment in data management infrastructure (World Bank, 2023). Second, carbon pricing may increase the cost of Tunisian exports entering the European market. According to IMF estimates, EU carbon prices could reach 70 to 95 euros per ton of CO₂ by 2030, significantly affecting the competitiveness of carbon-intensive industries (IMF, 2024a). (https://sl1nk.com/kJnOX) Third, CBAM may influence investment decisions within Tunisia’s industrial sector. Companies integrated into European supply chains may face increasing pressure to adopt low-carbon production technologies in order to maintain market access (OECD, 2023). In this sense, CBAM acts as an indirect carbon tax on Tunisia’s energy system and industrial structure. 2. Green Industrialisation as an Economic Necessity 2.1. Structural Weaknesses of Tunisia’s Industrial Model Tunisia’s industrial structure exhibits several characteristics that increase its vulnerability to carbon pricing mechanisms. Industrial production remains highly dependent on fossil fuels, particularly natural gas. Despite the country’s renewable energy potential, renewable sources still represent a relatively small share of total electricity generation (IEA, 2023). Many Tunisian manufacturing facilities also operate with aging infrastructure and limited technological modernisation. Energy efficiency levels remain lower than international benchmarks in several sectors. Furthermore, Tunisia’s industrial specialisation often focuses on medium-value-added manufacturing rather than high-technology sectors. This limits the capacity of firms to absorb additional environmental or regulatory costs (World Bank, 2024). These structural weaknesses increase exposure to CBAM-related risks. 2.2 Energy Transition as Industrial Strategy Although decarbonisation is often framed as an environmental objective, it increasingly represents an economic strategy. Tunisia possesses considerable solar and wind resources that could support a large-scale expansion of renewable energy production. Increasing renewable energy capacity would reduce the carbon intensity of electricity generation and strengthen the competitiveness of Tunisian industrial exports. Industrial energy efficiency improvements could also generate significant economic benefits. Investments in efficient equipment and production processes often reduce operational costs while lowering emissions (IEA, 2023). In addition, emerging sectors such as green hydrogen, renewable energy technologies, and low-carbon manufacturing could create new opportunities for industrial diversification (IRENA, 2023). 2.3 Integration into Euro-Mediterranean Green Value Chains The global transition toward low-carbon economies is creating new industrial value chains centred around renewable energy technologies, electric mobility, and sustainable materials. Tunisia’s geographic proximity to Europe and its established industrial base provide opportunities to participate in emerging Euro–Mediterranean green supply chains. By investing in renewable energy infrastructure and industrial innovation, Tunisia could attract foreign investment and strengthen its role in regional production networks (OECD, 2023). 3 Global Gateway and European Financial Instruments 3.1 The Global Gateway Strategy The European Union’s Global Gateway initiative aims to mobilise up to €300 billion in investments in sustainable infrastructure worldwide (European Commission, 2022). (https://sl1nk.com/tb0uO) The initiative focuses on strategic sectors including renewable energy, digital connectivity, transportation infrastructure, and climate resilience. Global Gateway combines public funding with private investment through mechanisms such as blended finance, guarantees, and development bank loans. 3.2 Financial Instruments Available to Tunisia Several European financial institutions support development projects in Tunisia, including the European Investment Bank (EIB) and the European Bank for Reconstruction and Development (EBRD). These institutions provide financing for renewable energy projects, industrial modernisation, and infrastructure development. Blended finance mechanisms combine grants and loans to reduce investment risks and mobilise private capital (OECD, 2023). 3.3 Current Limitations Despite the availability of financial instruments, several limitations remain. A significant share of climate-related financing is delivered through loans rather than grants, increasing the risk of climate-driven debt accumulation (IMF, 2023a). Furthermore, there is currently no explicit mechanism linking CBAM revenues to financial support for partner countries affected by the policy. This raises an important policy question: Can the EU impose carbon costs on imports without financing the decarbonisation of its trading partners? 4 From Carbon Tax to Development Opportunity Transforming CBAM into a development opportunity requires stronger alignment between European climate policy and development financing. From a climate justice perspective, developing economies emphasise the principle of common but differentiated responsibilities, which recognises differences in historical emissions and economic capacities (UNFCCC, 2015). In this context, international climate cooperation should include financial support, technology transfer, and capacity-building programmes. For Tunisia, several strategic priorities should guide negotiations with European partners: a. Ensuring national energy security before prioritising energy exports. b. Promoting local industrial participation in green infrastructure projects. c. Protecting fiscal sustainability and avoiding excessive debt. d. Strengthening transparency in climate-related investments. 5 Fiscal Implications and Budgetary Considerations 5.1 Fiscal Assessment of CBAM Impacts Beyond sectoral competitiveness, the Carbon Border Adjustment Mechanism (CBAM) is likely to generate significant indirect fiscal pressures for Tunisia. Tunisia’s vulnerability is closely linked to its energy structure. The country’s electricity system remains highly carbon-intensive, with approximately 85-90% of electricity generated from fossil fuels, primarily natural gas, and an estimated carbon intensity of 0.45–0.50 tCO₂/MWh (IEA, 2023; World Bank, 2023). (https://l1nq.com/VPJg4) Renewable energy represents less than 5% of electricity production, reflecting a significant gap compared to European decarbonisation levels (IEA, 2023).(https://sl1nk.com/0tZSZ) This carbon-intensive energy mix directly translates into higher embedded emissions in exported goods, which will be priced under CBAM (European Commission, 2023). CBAM is expected to affect Tunisia’s public finances through three main channels: Decline in export revenues: Carbon pricing between €70 and €95 per ton of CO₂ could increase production costs in exposed sectors by up to 20-30%, potentially reducing export competitiveness (OECD, 2023; IMF, 2024b). (https://sl1nk.com/zibya) Increased public investment needs: Tunisia aims to reach 30% renewable energy by 2030, requiring substantial investments in infrastructure and industrial decarbonisation (ANME, 2022). Energy-related fiscal pressures: Tunisia faces a structural energy deficit and high dependence on imported natural gas, which contributes to fiscal vulnerability and exposure to external shocks (World Bank, 2024). Cement Sector The cement sector is one of the most carbon-intensive industries, with emissions ranging between 0.6 and 0.9 tCO₂ per ton of cement (IEA, 2023). Tunisia’s reliance on petcoke and fossil fuels places it at the higher end of this range. Under a carbon price of €80/tCO₂, the additional cost could reach €50-70 per ton, significantly affecting export competitiveness (OECD, 2023). Fertilizer Sector Tunisia is a major producer of phosphate-based fertilizers, a sector characterised by emissions of 1.5 to 3 tCO₂ per ton of output, depending on production processes (World Bank, 2023).(https://l1nq.com/6HtgS) The sector’s dependence on natural gas and energy-intensive chemical transformations makes it particularly vulnerable to CBAM (IEA, 2023). Electricity Sector Electricity plays a central role in determining the carbon footprint of industrial production. Tunisia’s electricity mix is dominated by natural gas, resulting in carbon intensity levels significantly higher than the EU average (IEA, 2023; OECD, 2023). This creates a structural disadvantage, as electricity-related emissions are embedded in exported goods and increasingly accounted for under CBAM reporting requirements (European Commission, 2023). 5.2 Social Dimension and Just Transition The transition toward low-carbon industrialisation raises important social challenges. Employment risks are particularly concentrated in carbon-intensive sectors. According to international evidence, industrial decarbonisation can lead to short-term job displacement if not accompanied by reskilling policies (World Bank, 2023). In Tunisia, these risks are compounded by: regional inequalities, labour market rigidity, and limited access to green jobs. A just transition approach is therefore essential, including: vocational training programmes, targeted social protection, and inclusive policy design (UNFCCC, 2015). 5.3 Governance and Institutional Framework Effective CBAM adaptation requires strong governance frameworks. Current challenges in Tunisia include: limited coordination between industrial, energy, and fiscal policies, weak data systems for emissions tracking, and insufficient transparency in climate-related investments. Strengthening Monitoring, Reporting, and Verification (MRV) systems aligned with EU standards is essential (European Commission, 2023; World Bank, 2023). Moreover, integrating climate transition into medium-term fiscal frameworks is necessary to ensure sustainability (IMF, 2023b). 6 Strategic Policy Recommendations for Tunisia 6.1 Develop a Data-Driven National Industrial Decarbonisation Strategy Tunisia should prioritise CBAM-exposed sectors (cement, steel, fertilizers) based on quantified emissions and trade exposure. This strategy should include sector-specific targets, investment needs, and timelines, supported by scenario modelling to assess competitiveness impacts under different carbon price assumptions. 6.2 Integrate Climate Transition into Fiscal Policy and Budget Planning The government should incorporate climate transition costs into medium-term budget frameworks. This includes: reallocating inefficient fossil fuel subsidies, introducing green fiscal instruments, and mobilising international climate finance. A clear fiscal strategy is essential to balance industrial support, debt constraints, and social spending. 6.3 Accelerate Renewable Energy Deployment with Industrial Integration Beyond expanding renewable capacity, Tunisia should prioritise direct electrification of industry and long-term power purchase agreements (PPAs) to reduce carbon intensity in export-orientated sectors. 6.4 Strengthen MRV Systems with Sectoral Differentiation Tunisia should develop robust, sector-specific MRV frameworks aligned with EU standards. This requires institutional coordination, digital infrastructure, and capacity building, particularly for SMEs. 6.5 Promote a Just Transition Framework To mitigate social risks, Tunisia should implement: targeted reskilling programmes, regional development policies for affected industrial zones, and social protection measures for vulnerable workers. This will ensure that decarbonisation does not exacerbate inequalities. 6.6 Negotiate a Redistributive and Cooperative CBAM Framework with the EU Tunisia should advocate for: partial redistribution of CBAM revenues, increased grant-based climate finance, and facilitated access to low-carbon technologies. This cooperation should explicitly address fiscal asymmetries and development constraints. 6.7 Support Industrial Innovation and Green Value Chains Public policies should incentivise low-carbon innovation through tax incentives, green public procurement, and support for startups. Tunisia can position itself in emerging green value chains (e.g., green hydrogen, low-carbon materials). 7 Conclusion The Carbon Border Adjustment Mechanism represents a pivotal shift at the intersection of climate policy, international trade, and industrial transformation. For Tunisia, its implications are both constraining and potentially transformative. On the one hand, CBAM reveals and amplifies structural vulnerabilities within the country’s industrial model, notably its high carbon intensity and dependence on fossil fuels. It is likely to increase export costs, weaken the competitiveness of energy-intensive sectors, and generate additional fiscal and social pressures. On the other hand, the mechanism creates a powerful incentive to accelerate the transition toward a low-carbon and more resilient economic model, fostering industrial modernisation and integration into emerging green value chains. However, this transformation is contingent upon addressing three critical dimensions. First, financial sustainability remains a major constraint, given Tunisia’s limited fiscal space and rising debt levels, which restrict its capacity to finance large-scale decarbonisation efforts. Second, social inclusion must be ensured to prevent the transition from exacerbating existing inequalities, particularly in regions and sectors most exposed to structural change. Third, effective governance and accountability are essential to guarantee transparent, efficient, and equitable implementation of transition policies. In this context, the success of Tunisia’s response to CBAM will depend on its ability to align industrial strategy, fiscal policy, and social policy within a coherent and forward-looking transition framework. At the same time, it requires stronger international support in the form of concessional financing, technology transfer, and fairer cooperation mechanisms. Ultimately, without such alignment at both national and international levels, CBAM risks reinforcing existing asymmetries in global trade and creating new barriers for developing economies. Conversely, if embedded within a framework of climate justice and equitable burden sharing, it could serve as a catalyst for a more sustainable, competitive, and inclusive development pathway in Tunisia. References Agence Nationale pour la Maîtrise de l’Énergie (ANME). 2022. Stratégie nationale pour la transition énergétique à l’horizon 2030. Tunis. European Commission. 2022. Global Gateway Strategy. Brussels: European Commission. European Commission. 2023a. Carbon Border Adjustment Mechanism (CBAM). Brussels: European Commission. European Commission. 2023b. Carbon Border Adjustment Mechanism Regulation. Brussels: European Commission. European Commission. 2023c. EU Emissions Trading System (EU ETS). Brussels: European Commission. International Energy Agency (IEA). 2023a. Energy Policy Review: Tunisia 2023. Paris: IEA. International Energy Agency (IEA). 2023b. Energy Technology Perspectives 2023. Paris: IEA. International Monetary Fund (IMF). 2023a. Fiscal Monitor: Climate Policies and Public Finances. Washington, DC. International Monetary Fund (IMF). 2023b. Fiscal Policies for a Low-Carbon Economy. Washington, DC. International Monetary Fund (IMF). 2024a. World Economic Outlook: Climate Policies and Economic Transition. Washington, DC. International Monetary Fund (IMF). 2024b. Global Carbon Pricing Developments and Outlook. Washington, DC. International Renewable Energy Agency (IRENA). 2023. Renewable Energy Market Analysis: Middle East and North Africa. Abu Dhabi: IRENA. Organisation for Economic Co-operation and Development (OECD). 2023a. The Carbon Border Adjustment Mechanism: Implications for developing countries. Paris: OECD Publishing. Organisation for Economic Co-operation and Development (OECD). 2023b. The Economic Implications of the EU Carbon Border Adjustment Mechanism. Paris: OECD Publishing. United Nations Framework Convention on Climate Change (UNFCCC). 2015. Paris Agreement. Bonn: UNFCCC. World Bank. 2023. State and Trends of Carbon Pricing 2023. Washington, DC. World Bank 2024. MENA Economic Update: Green Industrial Transformation. Washington, DC. Zachmann, G., Roth, A. and Tamara, S. 2020. Preparing a Carbon Border Adjustment Mechanism in the EU. Bruegel Policy Contribution This report has been published by the Inclusive Society Institute The Inclusive Society Institute (ISI) is an autonomous and independent institution that functions independently from any other entity. It is founded for the purpose of supporting and further deepening multi-party democracy. The ISI’s work is motivated by its desire to achieve non-racialism, non-sexism, social justice and cohesion, economic development and equality in South Africa, through a value system that embodies the social and national democratic principles associated with a developmental state. It recognises that a well-functioning democracy requires well-functioning political formations that are suitably equipped and capacitated. It further acknowledges that South Africa is inextricably linked to the ever transforming and interdependent global world, which necessitates international and multilateral cooperation. As such, the ISI also seeks to achieve its ideals at a global level through cooperation with like-minded parties and organs of civil society who share its basic values. In South Africa, ISI’s ideological positioning is aligned with that of the current ruling party and others in broader society with similar ideals. Email: info@inclusivesociety.org.za Phone: +27 (0) 21 201 1589 Web: www.inclusivesociety.org.za

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The Evidence Says So IOL Up Jul 16, 2026 Why SA’s special economic zones look great on paper but fail in reality Daily Maverick Up Jul 15, 2026 AvSA aan Amerikaanse Ambassadeur: Afrikaners praat nie met net een stem nie AvSA Up Jul 12, 2026 Scapegoat Republic: SA’s slow march back to separate development news24 Up Jul 10, 2026 Afrikaners vir SA aan Bozell: 'Almal is slagoffers' Die Papier Up Jul 10, 2026 We’re asking the wrong question about the future of multilateralism Daily Maverick Up Jul 9, 2026 A more accurate diagnosis The Witness Up Jul 8, 2026 South Africa’s public healthcare system has expanded, but patients still feel the strain joburg (etc) Up Jul 8, 2026 SA’s health system under strain, but far from collapsing Juta Medical BriefL Up Jul 8, 2026 True South Africa | South Africa's Public Healthcare System – More Capacity, But Not Enough IOL Up Jul 7, 2026 Openbare gesondheid in SA is beter as wat jy dink, swakker as wat dit kan wees Netwerk 24 Up Jul 7, 2026 Public Health System Shows Signs of Progress Health Matters Up Jul 7, 2026 The country that forgot its own lesson: Xenophobia, memory and the pass book that never quite left Mail & Guardian Up Jul 7, 2026 South Africa’s health system is struggling, not collapsing The Citizen Up Jul 6, 2026 The crime paradox: Better statistics, worse public perception The Citizen Up Jul 1, 2026 Civic groups demand urgent election reform before 2029 The Citizen Up Jul 1, 2026 True South Africa | South Africa's Health System Is Better Than You Think, Worse Than It Should Be IOL Up Jun 29, 2026 Why motorists who paid e-tolls should be refunded Business Day Up Jun 26, 2026 Waarom ons minder veilig voel as wat die ware syfers bewys Netwerk 24 Up Jun 25, 2026 Why South Africans feel less safe than the data suggests Cape Times Up Jun 25, 2026 Has Crime in South Africa Increased or Decreased in 30 Years? IOL on TikTok Up Jun 24, 2026 Crime rates fell since 1994 but South Africans still feel unsafe The Citizen Up Jun 23, 2026 True South Africa | Why South Africans Feel Less Safe Than The Data Suggests Cape Argus Up Jun 23, 2026 True South Africa | Why South Africans Feel Less Safe Than The Data Suggests Weekend Argus Up Jun 23, 2026 True South Africa | Why South Africans Feel Less Safe Than The Data Suggests IOL Up Jun 17, 2026 Unemployment: are we measuring the wrong thing? Business Day Up Jun 16, 2026 True South Africa | Crime, Fear, and the Difference Between Facts and Feelings African News Agency Up Jun 16, 2026 True South Africa | Crime, Fear, and the Difference Between Facts and Feelings IOL Up Jun 11, 2026 ‘Wes-Kaap kán afskei en dís hoe’ Netwerk 24 Up Jun 8, 2026 Cape independence: A response to Daryl Swanepoel - Phil Craig Politics Web Up Jun 5, 2026 Republiek van die Wes-Kaap? Dis g’n so eenvoudig Netwerk 24 Up Jun 4, 2026 African Integration Beyond Trade: When Africans become foreigners in Africa B&FT Online Up Jun 4, 2026 Cape Independence and the Ethics of Constitutional Misrepresentation IOL Up Jun 3, 2026 African Integration Beyond Trade - When Africans Become Foreigners in Africa All Africa Up May 13, 2026 Xenophobia grows in data vacuum while govt response stays reactive The Citizen Up May 9, 2026 South Africa on edge as ‘March and March’ protests fuel rising anti-migrant tensions IOL Up May 7, 2026 Political Opportunism Fanning the Flames of Afriphobia in South Africa. Sovereign Media Up May 6, 2026 Xenophobia: How South Africans are shooting themselves in the foot La Nouvelle Tribune Up May 4, 2026 New surge in xenophobic violence in South Africa Ouest France Up May 3, 2026 Investigation into the xenophobic crisis tearing South Africa apart Ivoire Diaspo Up May 2, 2026 As elections approach, South Africa grapples with xenophobic fervor Lareleve.ma Up May 2, 2026 As elections approach, South Africa grapples with xenophobic fervor le 360 Afrique Up Apr 30, 2026 Even if all foreigners left, SA would still face the same problem The Cape Independent Up Apr 29, 2026 March and March moves into Gauteng as anti-foreigner sentiment swells ahead of elections Daily Maverick Up Apr 24, 2026 Diplomatieke stramheid met VSA: Wat SA te doen staan Netwerk24 Up Apr 22, 2026 South Africa Must Choose Strategic Patience Over Imported Panic IOL Up Apr 21, 2026 South Africa Must Choose Strategic Patience Over Imported Panic African News Agency Up Apr 19, 2026 Beyond binaries — why NHI success depends on design, not ideology Daily Maverick Up Apr 17, 2026 The world needs a new bargain Pressreader Up Apr 16, 2026 NHI in SA: Are we designing a system that can sustain universal coverage? The Citizen Up Apr 10, 2026 Dís wat Suid-Afrika oor NGV by China kan leer Volksblad Up Apr 10, 2026 Dís wat Suid-Afrika oor NGV by China kan leer Netwerk24 Up Mar 31, 2026 SSARG in South Africa: Undoing a Legacy of 300 Years in 30 Years TISCH Global Jumbos Up Mar 30, 2026 Europe, Africa face moment of reckoning as global shifts expose limits of unequal partnership All Africa Up Mar 30, 2026 Europe, Africa face moment of reckoning as global shifts expose limits of unequal partnership Daily Maverick Up Mar 27, 2026 Hou by die feite in debatte oor minderhede in die land Netwerk 24 Up Mar 27, 2026 Hou by die feite in debatte oor minderhede in die land Volksblad Up Mar 26, 2026 Our Pride In Being South African Is The Glue That Holds Us Together Tech Financials Up Mar 19, 2026 How can South Africa build real social cohesion? eNCA Up Mar 18, 2026 South Africans want unity but doubt it is possible The Citizen Up Mar 9, 2026 South Africa’s social fabric is fragile, but it may be starting to mend Daily Maverick Up Mar 9, 2026 Economists call for an overhaul of Reserve Bank's MPC Daily Maverick Up Feb 21, 2026 Economists call for an overhaul of Reserve Bank's MPC Sunday Times Up Feb 21, 2026 Kan een skool meer as een taalgemeenskap huisves? Netwerk24 Up Feb 19, 2026 Roelof Botha: Wysig dié beleid en skep só werk Netwerk24 Up Feb 16, 2026 AI can deepen democracy, or destroy it — the choice is ours Daily Maverick Up Feb 11, 2026 Early childhood and early adolescent predictors of internalising symptoms in adolescents: findings from a longitudinal study in a high-risk South African environment Springer Nature Link Up Feb 5, 2026 The quiet innovation that could unlock mother-tongue education in SA Daily Maverick Up Jan 27, 2026 DARYL SWANEPOEL: Why the fear over losing Agoa may be overstated | SA News MyZA Up Jan 27, 2026 DARYL SWANEPOEL: Why the fear over losing Agoa may be overstated Business Day Up Jan 24, 2026 Free SA urges opposition to draft hate speech regulations, warns of threats to privacy and free expression The Star Up Jan 21, 2026 Why Africa’s terrorism crisis is a governance crisis first Daily Maverick Up Jan 21, 2026 Why Africa's Terrorism Crisis Is a Governance Crisis First All Africa Up Jan 21, 2026 Dispute over Greenland: Conflict Prevention Possibilities under the UN Charter Katoikos Up Jan 18, 2026 Klaus Kotzé: American primacy revised — terra nova in the 21st century Business Day Up Jan 13, 2026 Daryl Swanepoel: Het ons boedel oorgegee? Netwerk24 Up Jan 12, 2026 After the Scroll: A Reflection of South Africa's Mood and the Need for Rational Hope IOL Up Jan 12, 2026 After the Scroll: A Reflection of South Africa's Mood and the Need for Rational Hope Business Report Up Jan 11, 2026 2026 local elections: South Africa braces for a surge in hung councils IOL Up Jan 11, 2026 South Africa's municipal elections: The rise of hung councils and coalition governance Daily News Up Jan 9, 2026 When Words Wound the Nation: Social Media, Racism, and Social Cohesion African News Agency Up Jan 7, 2026 Right of Reply: Growth, equality and the question we keep avoiding BizNews Up Jan 7, 2026 Record high interest rates are a self-inflicted economic blow BusinessDay Up Up

Media Coverage - 2022 Dec, 2022 2021 Civil Society Organization Sustainability Index for Sub-Saharan Africa fhi360: 13th Edition - December 2022 Up Dec 20, 2022 South Africa can find inspiration in Denmark's social model Arbejdervevaegelsens Erhvervsrad Up Dec 16, 2022 55th national elective congress is a ‘watershed moment’ for the ANC: Ramaphosa Inside Politics: Phuti Mosomane Up Nov 09, 2022 D-Day for public to give feedback to NCOP on Electoral Amendment Bill NewsNaija Up Nov 09, 2022 D-Day for public to give feedback to NCOP on Electoral Amendment Bill Head Topics Up Nov 09, 2022 D-Day for public to give feedback to NCOP on Electoral Amendment Bill SABC News Up Nov 09, 2022 Kieswet-wysiging: SA ‘by dieselfde draaipunt as in 1994’ Netwerk24: Ané van Zyl Up Nov 09, 2022 Kieswet-wysiging: SA ‘by dieselfde draaipunt as in 1994’ Netwerk24: Ané van Zyl Up Nov 09, 2022 Kieswet-wysiging: SA ‘by dieselfde draaipunt as in 1994’ Netwerk24: Ané van Zyl Up Nov 09, 2022 Kieswet-wysiging: SA ‘by dieselfde draaipunt as in 1994’ Netwerk24: Ané van Zyl Up Nov 07, 2022 Feelings of Trust, Distrust and Risky Decision-Making in Political Office. An Experimental Study With National Politicians in Three Democracies Sage Journals: James Weinberg Up Nov 07, 2022 The South African welfare state must be implemented in stages, as and when the economy allows Daily Maverick: Daryl Swanepoel Up Nov 02, 2022 Democratising the United Nations – Namibian TN Live News Up Nov 01, 2022 Democratising the United Nations The Namibian: William Gumede Up Oct 27, 2022 A people-driven state is required for national renewal Head Topics: Klaus Kotzé Up Oct 27, 2022 A people-driven state is required for national renewal Mail & Guardian: Klaus Kotzé Up Oct 24, 2022 Is Treasury on the right track with fiscal consolidation over expansionary stimulus? World News: Daryl Swanepoel Up Oct 24, 2022 Is Treasury on the right track with fiscal consolidation over expansionary stimulus? Business Day: Daryl Swanepoel Up Oct 21, 2022 National Assembly approves Electoral Amendment Bill Free State Central News: Centra Up Oct 20, 2022 MEDIA RELEASE: National Assembly passes the Electoral Amendment Bill Parliament Up Oct 19, 2022 UN weaknesses threaten global rule of law Mail & Guardian: William GumedeABC News Up Oct 16, 2022 The world is on shaky ground right now – and South Africa is no different ABC News Up Oct 16, 2022 The world is on shaky ground right now – and South Africa is no different Banoyi: Daryl Swanepoel Up Oct 16, 2022 The world is on shaky ground right now – and South Africa is no different Daily Maverick: Daryl Swanepoel Up Oct 12, 2022 UN Security Council Reform: a new approach to reconstructing the international order 24/7news.africa: Daryl Swanepoel Up Oct 12, 2022 UN Security Council Reform: a new approach to reconstructing the international order IOL: Daryl Swanepoel Up Oct 06, 2022 Xenophobia threatens the foundation of our constitutional values The Mercury: Melanie Lue Up Oct 06, 2022 Xenophobia threatens the foundation of our constitutional values Pretoria News: Melanie Lue Up Oct 06, 2022 Xenophobia threatens the foundation of our constitutional values Cape Times: Melanie Lue Up Sep 21, 2022 Developing an effective response to addressing Xenophobia in SA - An ISI Roundtable Polity: Sashnee Moodley Up Sep 14, 2022 SA must pull up its socks or tourism rebound may be short-lived Business Day: Daryl Swanepoel Up Sep 09, 2022 Inclusive Society Institute's proposal on the National Health Insurance Bill Valley FM: Marianne Dekker & Daryl Swanepoel Up Sep 08, 2022 Challenges and solutions for local economic development in Ekurhuleni Business Day: Nondumiso Sithole Up Sep 05, 2022 Parliament deploying 'Stalingrad' tactics when it comes to electoral reform News24: Michael Louis Up Sep 05, 2022 Gee olie vir SA se ekonomiese ratkas RSG Op en Wakker: Daryl Swanepoel Up Sep 04, 2022 SA’s local weather change adaptation should faucet into indigenous knowledge Agadir Group Up Sep 04, 2022 SA’s local weather change adaptation should faucet into indigenous knowledge Intestex Up Sep 04, 2022 SA’s climate change adaptation and resilience must be province-specific and tap into indigenous knowledge Daily Maverick: Nolubabalo Lulu Magam Up Sep 04, 2022 Discussion | ANC | Party's future in governance Banoyi Up Sep 04, 2022 Discussion | ANC | Party's future in governance eNCA: Daryl Swanepoel Up Sep 02, 2022 Civil society insists on revision of the electoral system ZA News Live Up Sep 02, 2022 Civil society pushes for overhaul of the electoral system ENEWS Up Sep 02, 2022 Civil society pushes for overhaul of the electoral system The Citizen: Brian Sokutu Up Sep 02, 2022 If a general election were held tomorrow the ANC would win the elections with clear 50% Opera News Up Sep 02, 2022 ROAD TO 2024 ELECTIONS: If a general election were held tomorrow and turnout was good, the ANC would clear 50% – Inclusive Society Institute Head Topics Up Sep 02, 2022 ROAD TO 2024 ELECTIONS: If a general election were held tomorrow and turnout was good, the ANC would clear 50% – Inclusive Society Institute Flipboard Up Sep 02, 2022 If a general election were held tomorrow and turnout was good, the ANC would clear 50% – Inclusive Society Institute msn.com Up Sep 02, 2022 ROAD TO 2024 ELECTIONS: If a general election were held tomorrow and turnout was good, the ANC would clear 50% – Inclusive Society Institute Banoyi Up Sep 01, 2022 If a general election were held tomorrow and turnout was good, the ANC would clear 50% – Inclusive Society Institute iono.fm Up Sep 01, 2022 If a general election were held tomorrow and turnout was good, the ANC would clear 50% – Inclusive Society Institute Daily Maverick: Ferial Haffajee Up Aug 31, 2022 Türkiye holds panel on Security Council reform in Cape Town US Muslims: Murat Ozgur Guvendik Up Aug 31, 2022 Intellecturals condemn Africa's absence from UN Security Council and call for reform Al Jama-Ah Up Aug 31, 2022 Türkiye holds panel on UN reform in Cape Town TN Live News Up Aug 31, 2022 Turkiye Holds Panel On Security Council Reform In Cape Town IBC Tech Up Aug 31, 2022 Turkiye holds panel on Safety Council reform in Cape City The Times of Sindh Up Aug 31, 2022 Turkiye holds panel on Security Council reform in Cape Town Middle East Monitor Up Aug 31, 2022 Intellectuals condemn Africa’s absence from UN Security Council and call for reform IOL: Mwangi Githahu Up Aug 31, 2022 Panel calls for reform of UN Security Council Cape Argus: Mwangi Githahu Up Aug 31, 2022 Hierdie ratte kort net olie Die Burger: Daryl Swanepoel Up Aug 31, 2022 Hierdie ratte kort net olie Beeld: Daryl Swanepoel Up Aug 31, 2022 Hierdie ratte kort net olie Netwerk 24: Daryl Swanepoel Up Aug 31, 2022 "UN Security Council Reform" panel in Cape Town from the Presidency's Directorate of Communications Canli Gaste Up Aug 30, 2022 Appointment of anti-corruption council a critical step, but it must be given big teeth Banoyi Up Aug 30, 2022 Appointment of anti-corruption council a critical step, but it must be given big teeth Daily Maverick: Omphemetse S Sibanda Up Aug 30, 2022 Türkiye holds panel on UN reform in Cape Town Daily Sabah Up Aug 30, 2022 Türkiye holds panel on Security Council reform in Cape Town Salten News Up Aug 30, 2022 “UN Security Council Reform” Panel in Cape Town from the Presidency of Communications Guncel Haber Up Aug 30, 2022 “UN Security Council Reform” panel in Cape Town from the Presidency of Communications Samimi Haber Up Aug 30, 2022 "UN Security Council Reform" panel in Cape Town Ulak News Up Aug 30, 2022 'UN Security Council Reform' in Cape Town from the Presidency's Directorate of Communications Filodyo: Yayin Tarihi Up Aug 30, 2022 'UN Security Council Reform' panel in Cape Town from the Presidency of Communications Ankaradan Haber Up Aug 30, 2022 'UN Security Council Reform' in Cape Town from the Presidency's Directorate of Communications Dik Gazete Up Aug 30, 2022 ”UN Security Council Reform” panel in Cape Town from the Presidency of Communications Muhalif Up Aug 30, 2022 "UN Security Council Reform" panel in Cape Town from the Presidency's Directorate of Communications Son Dakika Up Aug 30, 2022 'UN Security Council Reform' panel in Cape Town from the Presidency of Communications Anadolu Ajansi: Murat Ozgur Guvendik Up Aug 30, 2022 "UN Security Council Reform" panel in Cape Town Son Haberler Up Aug 22, 2022 Grease the gears so the economic wheels can turn Head Topics: Daryl Swanepoel Up Aug 22, 2022 Grease the gears so the economic wheels can turn Business Day: Daryl Swanepoel Up Jul 25, 2022 Solving For The Workplace Of The Future The Skills Portal Up Jul 24, 2022 Social cohesion and the factors influencing unity with the South African society Valley FM: Marianne Dekker & Daryl Swanepoel Up Jul 22, 2022 Solving for the workplace of the future FA News Up Jul 22, 2022 Inclusive Society Institute on crime in SA The Voice of the Cape: Daryl Swanepoel Up Jul 22, 2022 Recent tavern killings show crippling inability to tackle rising crime IOL: Sisipho Bhuta Up Jul 21, 2022 Skills supply and skills demand in the South African economy Nexford University: Mark Talmage-Rostron Up Jul 14, 2022 Crime and chaos in communities Banoyi: eNCA interview with Daryl Swanepoel Up Jul 14, 2022 Crime and chaos in communities eNCA: Gareth Edwards speaks to Daryl Swanepoel Up Jul 12, 2022 Five ways in which South Africa can advance equity Daily Maverick: Rose Tuyeni Peter, Beth Vale and Daryl Swanepoel Up Jul 05, 2022 Authorities must regain belief of the individuals of South Africa USA News Love Up Jul 05, 2022 Anti-Corruption Cape Talk - Afternoon Drive with John Maytham: Prof Zweli Ndevu Up Jul 04, 2022 Government needs to regain trust of the people of South Africa - and that means acting against corruption Daily Maverick: Evangelos Mantzaris and Daryl Swanepoel Up Jun 27, 2022 Towards a national commitment Business Day: Klause Kotzé Up Jun 19, 2022 Les fissures se creusent au sein du parti au pouvoir sud-africain ANC Wazakin Up Jun 18, 2022 Cracks widen in South African ruling party ANC Newshunter365 Up Jun 18, 2022 Cracks widen in South African ruling party ANC The East African: Peter Dube Up Jun 14, 2022 Songezo Zibi says he will run for president... FR Postsus Up Jun 14, 2022 South African Politics Sparks New Direction As ANC Reaches Its End-of-life Date, New Generation Leaders Emerge Global Upfront Newspapers Up Jun 14, 2022 Songezo Zibi says he will run for president as he tables a manifesto for a new society; more will follow Daily Maverick: Ferial Haffajee Up Jun 12, 2022 Time is ripe for electoral change in SA Sunday Times: Mmusi Maimane Up Jun 08, 2022 Anti-corruption dialogue with Professor Thuli Madonsela We can change our world Up Jun 02, 2022 Civil society criticizes Parliament for not respecting its constitutional obligations News Post Us Zero: Deborah Up Jun 02, 2022 Electoral Amendment Bill: Civil society slams Parliament for not meeting constitutional obligations Banoyi: News24.com Up Jun 01, 2022 Civil society groups agree on steps to change electoral system before 2024 elections Gateway News Up Jun 01, 2022 Electoral Amendment Bill: Civil society slams Parliament for not meeting constitutional obligations The World News Up Jun 01, 2022 Electoral Amendment Bill: Civil society slams Parliament for not meeting constitutional obligations News24: Jan Gerber Up May 31, 2022 The Electoral Amendment Bill Cape Talk: John Maytham interviews Daryl Swanepoel Up May 25, 2022 Get back to basics to reboot growth Business Day: Daryl Swanepoel Up May 25, 2022 Get back to basics to reboot growth Head Topics: Daryl Swanepoel Up May 25, 2022 Without social justice, social cohesion can only be a temporary, ephemeral concept Daily Maverick: Dr Klaus Kotzé Up May 25, 2022 Without social justice, social cohesion can only be a temporary, ephemeral concept Banoyi Up May 25, 2022 Without social justice, social cohesion can only be a temporary, ephemeral concept iono.fm: Daily Maverick Up May 24, 2022 Employment Services Amendment Bill The Voice of the Cape: Interview with Daryl Swanepoel Up May 23, 2022 Nation Building: Racial inequality in South Africa eNCA: Mfundo Mabalane interviews Daryl Swanepoel Up May 18, 2022 Here Is Why SA Citizens Hate Immigrants Opera News Up May 15, 2022 SA citizens don’t trust immigrants, says survey Trumpet International Magazine: Omotayo Daranjo Up May 14, 2022 Naweekaktueel: Meer as 10% gekwalifiseerde Suid-Afrikaners wil immigreer RSG: Anita Visser voer onderhoud met Daryl Swanepoel Up May 14, 2022 South Africans don't trust immigrants, survey reveals News 365: Omie Chester Up May 13, 2022 Brain drain | Skilled workers may leave in a year or two eNCA: Tumelo Mothotoane interviews Daryl Swanepoel. Up May 13, 2022 South Africans don't trust foreigners - Survey reveals Celebrity Breeze Up May 13, 2022 SA citizens don't trust immigrants, says survey IOL Up May 13, 2022 'Fix the economy' - warns institute amid study showing high number of South Africans want to emigrate IOL Up May 13, 2022 'Fix the economy' - warns institute amid study showing high number of South Africans want to emigrate Scalabrini Institute for Human Mobility in Africa Up May 13, 2022 'Fix the economy' - warns institute amid study showing high number of South Africans want to emigrate MTNPlay (IOL article) Up May 13, 2022 'Fix the economy' - warns institute amid study showing high number of South Africans want to emigrate Hebdenbridge News Up May 13, 2022 Over 10% of South Africans with higher education qualifications are considering emigrating: Study Newzroom Africa: Daryl Swanepoel Up May 12, 2022 Big brain drain alert: Over 10% of educated South Africans want to emigrate African News Agency: Molaole Montsho Up May 12, 2022 Big brain drain alert: Over 10% of educated South Africans want to emigrate IOL Up May 10, 2022 Structural reform across the board needed to pave way for SA welfare state Daily Maverick: Dr Klaus Kotzé Up May 10, 2022 Structural reform across the board needed to pave way for SA welfare state Banoyi: Dr Klaus Kotzé Up May 06, 2022 South Africans don't trust foreigners of any origin Mail & Guardian: Bongeka Gumede Up Apr 27, 2022 SA citizens no longer trust immigrants - says new survey Opera News Up Apr 24, 2022 SA citizens don't trust immigrants, says survey Weekend Argus: Brenda Masilela Up Apr 18, 2022 Efficient logistics needed to keep agri exports on the right track World News: Daryl Swanepoel Up Apr 18, 2022 Efficient logistics needed to keep agri exports on the right track Business Day: Daryl Swanepoel Up Apr 16, 2022 African nations must base foreign policy on domestic interests, not past ideological ties Ramadan-Karim: Rosanna H. Brooks Up Apr 16, 2022 African nations must base foreign policy on domestic interests, not past ideological ties The Namibian: William Gumede Up Apr 14, 2022 Artistic concepts of hope can scale back inequality in South Africa The Indian Express: Anja Smith, Jodi Wishnia, Carmen Christian & Daryl Swanepoel Up Apr 13, 2022 We have to be creative and harness ideas of hope to reduce inequality in South Africa Daily Maverick: Anja Smith, Jodi Wishnia, Carmen Christian & Daryl Swanepoel Up Apr 13, 2022 Creative ideas of hope can reduce inequality Articleslider: Anja Smith, Jodi Wishnia, Carmen Christian & Daryl Swanepoel Up Apr 12, 2022 The Russia-Ukraine War: What has been the impact on South Africa and fellow BRICS (Brasil, Russia, India, China, SA) members and on African economies ResearchGate: William Gumede Up Apr 11, 2022 African nations must base foreign policy on hame care ... newsfounded.com: William Gumede Up Apr 11, 2022 African nations must base foreign policy on domestic interests, not past ideological ties Daily Maverick: William Gumede Up Apr 11, 2022 Graft still a big problem The Citizen: Daryl Swanepoel Up Apr 11, 2022 Little done to bring the thieves to book The World News Up Apr 11, 2022 Little done to bring the thieves to book The Citizen: Editorial Up Apr 02, 2022 'Apartheid was 'n welsynstaat vir wit mense' Die Burger: Murray La Vita Up Apr 02, 2022 'Apartheid was 'n welsynstaat vir wit mense' Netwerk24: Murray La Vita Up Apr 01, 2022 Die Burger se praat saam-diskoersreeks - Hoe floreer die private sektor in 'n welsynstaat? KKNK 2022 Gesprekke Up Mar 31, 2022 Rejuvenating SA's economy - a labour sector perspective Business Day: Daryl Swanepoel Up Mar 29, 2022 Es probable que Ramaphosa gane la conferencia electiva del ANC ES Postsus Up Mar 28, 2022 Ramaphosa likely to win ANC elective conference and lead a coalition government in 2024 - research reports Daily Maverick: Ferial Haffajee Up Mar 23, 2022 Media statement: Home Affairs Committee concludes countrywide public consultation process RSA Parliament: Media Statement Up Mar 23, 2022 Discussions to fix Eskom's woes IOL: Ntombi Nkosi Up Mar 22, 2022 Conditions needed in a society to enable it to advance towards a welfare state The Voice of the Cape: Interview with Dr Klaus Kotzé Up Mar 18, 2022 Crisis in Europe highlights critical importance of selfsufficient, secure and stable energy production Business Day: Daryl Swanepoel Up Mar 13, 2022 Government must get back to basics to build a better economy Head Topics: Business Day - Daryl Swanepoel Up Mar 13, 2022 Government must get back to basics to build a better economy Business Day: Daryl Swanepoel Up Mar 06, 2022 Inclusive Society Institute says Electoral Bill does not respond to society's expectations for fundamental electoral reform Independent Candidate Association South Africa Up Mar 06, 2022 Inclusive Society Institute says Electoral Bill does not respond to society's expectations for fundamental electoral reform IOL: Mayibongwe Maqhina Up Mar 02, 2022 New Electoral Amendment Bill slated Oudtshoorn Courant: Citizen reporter Up Mar 02, 2022 New Electoral Amendment Bill slated George Hearld: Source Citizen reporter Up Mar 02, 2022 Media statement: Home Affairs Committee assures South Africans about a meaningful public participation process to be undertaken RSA Parliament: Media statement Up Mar 01, 2022 New Electoral Amendment Bill slated The Citizen: Article by Lunga Simelane Up Mar 01, 2022 New Electoral Amendment Bill slated The Daily Mirror: Article by Tshepo Mohale Up Mar 01, 2022 SA's electoral system is ripe for radical change, OSA tells Parliament News24: Article by Jason Felix Up Mar 01, 2022 New Electoral Amendment Bill slated The Citizen: Lunga Simelane Up Mar 01, 2022 Ubuntu and the role of the State Transform: Dr Motsamai Molefe Up Feb 21, 2022 What the ANC can learn from Singapore's People's Action Party Business Day: Opinion piece by Prof William Gumede Up Feb 15, 2022 Reuse tekort aan digitale vaardighede in Suid-Afrika KykNET Verslag: Ilze-Marie Le Roux gesels met kenners oor wat aget die tekort steek en hoe dit aangespreek kan word Up Feb 13, 2022 Social democracy - A pathway for South Africa's development Africa Press Up Feb 13, 2022 Social democracy - A pathway for South Africa's development Opera News article by Carole-Tee Up Feb 13, 2022 Social democracy - A pathway for South Africa's development IOL article by Dr Klaus Kotzé Up Feb 10, 2022 Can South Africa afford the NHI? 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POPI Policy Protection of personal information policy 1. Policy statement 1.1. The Inclusive Society Institute processes personal information of its employees, members, clients, suppliers, and other data subjects from time to time. As such, it is obliged to comply with the Protection of Personal Information Act No. 4 of 2013 (“POPIA”) as well as the Promotion of Access to Information Act No. 2 of 2000 (“PAIA”). 1.2 In line with this, the Inclusive Society Institute is committed to protecting its members’/clients’/supplier’s/employees’ and other data subjects’ privacy and ensuring that their personal information is used appropriately, transparently, securely and in accordance with applicable laws. 1.3 This Policy sets out the manner in which the Inclusive Society Institute deals with such personal information and provides clarity on the general purpose for which the information is used, as well as how data subjects can participate in this process in relation to their personal information. 1.4 In addition to this policy, the institute has also developed a manual and made it available as prescribed under the PAIA Act. Where parties/requesters submit requests for information disclosure in terms of this manual, internal measures have been developed, together with adequate systems to process requests for information or access thereto. 2. Objectives 2.1. To ensure legislative compliance (POPIA and PAIA ) in respect of all personal information that the Inclusive Society Institute collects and processes. 2.2. To inform employees and clients as to how their personal information is used, disclosed and destroyed. 2.3. To ensure that personal information is only used for the purpose for which it was collected. 2.4. To prevent unauthorised access to and use of personal information. 3. Definitions 3.1. “Biometric information” means the physical, physiological, or behavioural identification, including finger printing, amongst others. 3.2. “Processing” means: 3.2.1. The collection, receipt, recording organisation, collation, storage, updating, modification, retrieval, alteration, consultation or use; 3.2.2. Dissemination by means of transmission, distribution or making available in any form; 3.2.2. Merging, linking, erasure or destruction of information. 3.3. “PAIA” means the Promotion of Access to Information Act No. 2 of 2000. 3.4. “POPIA” means the Protection of Personal Information Act No. 4 of 2013. 3.5. “Regulator” means the Information Regulator established in terms of POPIA. 4. Collection of personal information 4.1. The Inclusive Society Institute collects and processes various items of information pertaining to its employees, members, clients, suppliers and other data subjects. The information collected is based on need and it will be processed for that need/purpose only. Whenever possible, the Inclusive Society Institute will inform the relevant party of the information required (mandatory) and which information is deemed optional. 4.2. The employee, member or client will be informed of the consequence/s of failing to provide such personal information and any prejudice which may be incurred due to non-disclosure. For example, the Inclusive Society Institute may not be able to employ an individual without certain personal information relating to that individual or the organisation may not be in a position to render services to a client in the absence of certain information which is required. 4.3. The Inclusive Society Institute will process information in a manner that is lawful and reasonable (i.e., will not infringe the privacy of the individual or company). 4.4. Where consent is required for the processing of information, such consent will be obtained. 4.5. Information will be processed under the following circumstances: 4.5.1. When carrying out actions for the conclusion or performance of a contract; 4.5.2. When complying with an obligation imposed by law on the Institute; 4.5.3. For the protection of a legitimate interest of the data subject; 4.5.4. Where necessary, for pursuing the legitimate interests of the Institute or of an authorised third party to whom the information is supplied. 4.6. Examples of the personal information the Inclusive Society Institute collects includes, but is not limited to: 4.6.1. Information relating to the race, gender, sex, pregnancy, marital status, national, ethnic or social origin, colour, sexual orientation, age, physical or mental health, well-being, disability, religion, conscience, belief, culture, language and birth of an employee; 4.6.2. Information relating to the education or the medical, financial, criminal or employment history (this includes disciplinary action) of an employee; 4.6.3. Banking and account information; 4.6.4. Contact information; 4.6.5. Trade union membership and political persuasion; 4.6.6. Any identifying number, symbol, email address, telephone number, location information, online identifier or other particular assignment related to the employee, member or client; 4.6.7. The biometric information of the employee, member, client or data subject; and 4.6.8. The personal opinions, views or preferences of an employee (also performance appraisals or correspondence) and the views or opinions of another individual about the person. 4.7. The Inclusive Society Institute shall not process special personal information without complying with the specific provisions of the POPI Act. Special information includes personal information concerning: 4.7.1. the religious or philosophical beliefs, race or ethnic origin, trade union membership, political persuasion, health, sex life or biometric information of a data subject; or 4.7.2. the criminal behaviour of a data subject, where such information relates to the alleged commission by a data subject of any offence committed or the disposal of such proceedings 4.8. Collection of employee information: 4.8.1. For the purposes of this Policy, employees include potential, past and existing employees of the Inclusive Society Institute. Independent contractors are treated on the same basis where the collection of information is concerned. 4.8.2. When appointing new employees/contractors, the Inclusive Society Institute requires information, including, but not limited to that listed above, from prospective employees/contractors, in order to process the information on the system/s. Such information is reasonably necessary for the Institute’s record purposes, as well as to ascertain if the prospective employee/contractor meets the requirements, for the position which he/she is being appointed to/contracted for and is suitable for appointment. 4.8.3. The Inclusive Society Institute will use and process such employee information, as set out below, for purposes including, but not limited to, its employment records and to make lawful decisions in respect of that employee and its business. 4.8.4. Use of employee information: Employees’ personal information will only be used for the purpose for which it was collected and intended. This includes, but is not limited to: 4.8.4.1. Submissions to the Department of Labour; 4.8.4.2. Submissions to the Receiver of Revenue; 4.8.4.3. For audit and recordkeeping purposes; 4.8.4.4. In connection with legal proceedings; 4.8.4.5. In connection with and to comply with legal and regulatory requirements; 4.8.4.6. In connection with any administrative functions of the Institute; 4.8.4.7. Disciplinary action or any other action to address the employee’s conduct or capacity; 4.8.4.8. In respect of any employment benefits that the employee is entitled to; 4.8.4.9. Pre- and post-employment checks and screening; and 4.8.4.10. Any other relevant purpose of which the employee has been notified. 4.8.5. Should information be processed for any other reason; the employee will be informed accordingly. Collection of 4.9. Collection of Member/Client/Supplier information: 4.9.1. For purposes of this Policy, clients include potential, past and existing members and clients. Suppliers include all vendors which contract with the Inclusive Society Institute, whether once off or recurring, in respect of products and services. 4.9.2. The Inclusive Society Institute collects and processes its members’, clients’ and suppliers’ personal information, such as that mentioned hereunder. The type of information will depend on the need for which it is collected and will be processed for that purpose only. Further examples of personal information collected from clients include, but is not limited to: 4.9.3. The Inclusive Society Institute also collects and processes member/clients’ personal information for marketing purposes in order to ensure that its products and services remain relevant to its clients and potential clients. 4.9.4. Use of member/client/supplier information: 4.9.4.1. The member/client/supplier’s personal information will only be used for the purpose for which it was collected and as agreed. This may include, but not be limited to: 4.9.4.2. Providing products or services to members/clients; 4.9.4.3. In connection with sending accounts and communication to a member/client in respect of services rendered; 4.9.4.4. Payment of suppliers and communication in respect of services rendered; 4.9.4.5. Referral to other service providers; 4.9.4.6. Confirming, verifying and updating member/client/supplier details; 4.9.4.7. Conducting market or customer satisfaction research; 4.9.4.8. For audit and record keeping purposes; 4.9.4.9. In connection with legal proceedings; and 4.9.4.10. In connection with and to comply with legal and regulatory requirements or when it is otherwise allowed by law. 4.10. Disclosure of personal information 4.10.1. The Inclusive Society Institute may share employees’ and member/clients/suppliers’ personal information with authorised third parties as well as obtain information from such third parties for reasons set out above. 4.10.2. The Inclusive Society Institute may also disclose employees’ or member/clients/suppliers’ information where there is a duty or a right to disclose in terms of applicable legislation, the law or where it may be necessary to protect the rights of the organisation or it is in the interests of the data subject. 5. Safeguarding of personal information and consent 5.1. The Inclusive Society Institute shall review its security controls and processes on a regular basis to ensure that personal information is secure. 5.2. It will take appropriate, reasonable technical and organisational measures to prevent loss or damage or unauthorised destruction of personal information, and unlawful access to or processing of personal information. This will be achieved by – 5.2.1. Identifying internal and external risks; 5.2.2. Establishing and maintaining appropriate safeguards; 5.2.3. Regularly verifying these safeguards and their implementation; 5.2.4. Updating the safeguards; and 5.2.5. Implementing generally accepted information security practices and procedures. 5.3. The Inclusive Society Institute shall appoint an Information Officer and Deputy Information Officer who is/are responsible for compliance with the conditions of the lawful processing of personal information and other provisions of POPIA. 5.3.1. Information Officer details 5.3.1.1. Information Officer Name: Daryl Swanepoel, Chief Executive Officer Telephone number: 021 201 1589 Postal address: P O Box 12609, Mill Street, Cape Town, 8010 Physical address: 1006 One Thibault, 1 Thibault Square, Cape Town, 8001 Email address: ceo@inclusivesociety.org.za 5.3.1.2. Deputy Information Officer Name: Edwin Mc Queen, Corporate Services Officer Telephone number: 021 201 1589 Postal address: P O Box 12609, Mill Street, Cape Town, 8010 Physical address: 1006 One Thibault, 1 Thibault Square , Cape Town, 8001 Email address: admin@inclusivesociety.org.za 5.4. The specific responsibilities of the Information Officer and his/her Deputy include – 5.4.1. The development, implementation, monitoring and maintenance of a compliance framework; 5.4.2. The undertaking of a personal information impact assessment to ensure that adequate measures and standards exist in order to comply with the conditions for the lawful processing of personal information; 5.4.3. The development, monitoring and maintenance of a manual, as well as the making available thereof, as prescribed in section 51 of the Promotion of Access to Information Act, 2000 (Act No. 2 of 2000); 5.4.4. The development of internal measures, together with adequate systems, to process requests for information or access thereto; and 5.4.5. To ensure that Institute staff awareness sessions are conducted regarding the provisions of the Act, regulations made in terms of the Act, codes of conduct, or information obtained from the Regulator. 5.5. Employment contracts/addendums thereto, containing relevant consent clauses for the use and storage of employee information, or any other action so required, in terms of POPIA, must be signed by every employee. 5.6. On an ongoing basis, all suppliers, insurers and other third-party service providers are required to sign a service level agreement guaranteeing their commitment to the Protection of Personal Information. 5.7. Consent to process client/member/supplier information is obtained from clients/members (or a person who has been given authorisation from the client/member to provide the client/member’s personal information) and suppliers at sign on/appointment/contracting. 6. Direct marketing 6.1. The institute shall ensure that: 6.1.1. It does not process any personal information for the purpose of direct marketing (by means of any form of electronic communication, including automatic calling machines, SMS’s or e-mail) unless the data subject has given his, her or its consent to the processing, or is an existing customer. 6.1.2. It will only approach data subjects, whose consent is required and who have not previously withheld such consent, once in order to request the consent. This will be done in the prescribed manner and form. 6.1.3. The data subjects will only be approached for the purpose of direct marketing of the Inclusive Society Institute’s own products or services. In all instances, the data subject shall be given a reasonable opportunity to object, free of charge and in a manner free of unnecessary formality, to such use of his, her or its electronic details at the time when the information is collected. 6.1.4. Any communication for the purpose of direct marketing will contain details of the identity of the sender or the person on whose behalf the communication has been sent and an address or other contact details to which the recipient may send a request that such communications cease. 7. Transfer of information outside of South Africa 7.1. The Inclusive Society Institute will not transfer personal information about a data subject to a third party who is in a foreign country unless one or more of the following apply: 7.1.1. the third party is subject to a law, binding corporate rules or a binding agreement which provides an adequate level of protection of personal information and effectively upholds principles for reasonable processing of the information; 7.1.2. the data subject consents to the transfer; 7.1.3. the transfer is necessary for the performance of a contract between the data subject and the Institute; 7.1.4. the transfer is necessary for the conclusion or performance of a contract concluded in the interest of the data subject between the Institute and a third party; or 7.1.5. the transfer is for the benefit of the data subject, and it is not reasonably practicable to obtain the consent of the data subject to that transfer and if it were reasonably practicable to obtain such consent, the data subject would be likely to give it. 8. Recording systems 8.1. Video footage and/or voice/telephone calls that have been recorded, processed and stored constitute personal information. As such the Inclusive Society Institute will make all employees, members, clients or data subjects aware as to the use of any recording systems. 9. Security breaches 9.1. Should the Inclusive Society Institute detect a security breach on any of its systems that contain personal information, it shall take the required steps to assess the nature and extent of the breach in order to ascertain if any information has been compromised. 9.2. The Inclusive Society Institute shall notify the affected parties should it have reason to believe that their information has been compromised. Such notification shall only be made where the organisation can identify the data subject to which the information relates. Where it is not possible it may be necessary to consider website publication and whatever else the Information Regulator prescribes. 9.3. Notification will be provided in writing by means of either: 9.3.1. Email; 9.3.2. registered mail; or 9.3.3. the organisation’s website 9.4. The notification shall provide the following information where possible: 9.4.1. Description of possible consequences of the breach; 9.4.2. Measures taken to remedythe breach; 9.4.3. Recommendations to be taken by the data subject to mitigate adverse effects; and 9.4.4. The identity of the party responsible for the breach. 9.5. In addition to the above, the Inclusive Society Institute shall notify the Regulator of any breach and/or compromise to personal information in its possession and work closely with and comply with any recommendations issued by the Regulator. 9.6. The following will apply in this regard: 9.6.1. The Information Officer will be responsible for overseeing the investigation; 9.6.2. The Information Officer will be responsible for reporting to the Information Regulator within 3 working days of a breach/ compromise to personal information; 9.6.3. The Information Officer will be responsible for reporting to the Data Subject(s) within 3 working days, as far as is reasonable and practicable, of a breach/ compromise to personal information. 9.6.4. The timeframes above are guidelines and depending on the merits of the situation may require earlier or later reporting. 10. Access and correction of personal information 10.1. Employees and members/clients have the right to request access to any personal information that the Inclusive Society Institute holds about them. 10.2.Employees and members/clients have the right to request the Inclusive Society Institute to update, correct or delete their personal information on reasonable grounds. Such requests must be made to the Information Officer (see details above) or to the Inclusive Society Institute’s head office (see details below). 10.3. Where an employee or member/client objects to the processing of their personal information, the Inclusive Society Institute may no longer process said personal information. The consequences of the failure to give consent to process the personal information must be set out before the employee or client confirms his/her objection. 10.4. The member/client or employee must provide reasons for the objection to the processing of his/her personal information. 10.4.1 Head office details 10.4.2 Name: Inclusive Society Institute 10.4.3 Telephone number: 021 201 1589 10.4.4 Postal address: Box 12609, Mill Street, Cape Town, 8010 10.4.5 Physical address: 1006 One Thibault, 1 Thibault Square , Cape Town, 8001 10.4.6 Email address: admin@inclusivesociety.org.za 11. Retention of records 11.1. The Inclusive Society Institute is obligated to retain certain information, as prescribed by law. This includes but is not limited to the following: 11.1.1. With regard to the Companies Act No. 71 of 2008 and the Companies Amendment Act No. 3 of 2011, hard copies of the documents mentioned below must be retained for 7 years: 11.1.2. Any documents, accounts, books, writing, records or other information that a company is required to keep in terms of the Act; 11.1.3. Notice and minutes of all meetings, including resolutions adopted; 11.1.4. Copies of reports presented at the annual general meeting; and 11.1.5. Copies of annual financial statements required by the Act and copies of accounting records as required by the Act. 11.2. The Basic Conditions of Employment Act No. 75 of 1997, as amended, requires the organisation to retain records relating to its staff for a period of no less than 3 years. 12. Amendments to this policy 12.1. Amendments to this Policy will take place from time to time subject to the discretion of the Inclusive Society Institute and pursuant to any changes in the law. Such changes will be brought to the attention of employees, members and clients where it affects them. 13. Requests for information 13.1. In terms of requests to be processed under POPIA, the following forms shall be used – 13.1.1. Objection to the processing of personal information – a data subject who wishes to object to the processing of personal information in terms of section 11(3)(a) of the Act, must submit the objection to the responsible party. 13.1.2. Request for correction or deletion of personal information or destruction or deletion of record of personal information – a data subject who wishes to request a correction or deletion of personal information or the destruction or deletion of a record of personal information in terms of section 24(1) of the Act, must submit a request to the responsible party. 13.1.3. Request for data subject’s consent to process personal information – a responsible party who wishes to process the personal information of a data subject for the purpose of direct marketing by electronic communication must submit a request for written consent to that data subject. 13.1.4. Submission of complaint – Any person who wishes to submit a complaint contemplated in section 74(1) of the Act must submit such a complaint to the Regulator on Part I of Form 5. A responsible party or a data subject who wishes to submit a complaint contemplated in section 74(2) of the Act must submit such a complaint to the Regulator on Part II. 13.2. In terms of requests for information under PAIA, the provisions of the PAIA Sec 51 Manual must be complied with. 13.3. Any requests and/ or advice can be directed to the Information Officer set out in this policy and in the Sec 51 PAIA manual.