Complexity and Critical Thought: Inference at the Edge of Chaos
Notice bibliographique
Résumé
This dissertation reconceptualizes critical thought as an emergent phenomenon within a complex adaptive system of inference. Highlighting the dynamic, self-organizing nature of human reasoning provides the foundation for introducing the concept of inferential criticality and describing the associated activity of critical inference. Rather than treating critical thinking as a fixed set of cognitive skills and dispositions, this research argues that it is best understood as an adaptive process that unfolds within uncertain and evolving epistemic environments. Drawing from research on active inference and complexity science, the study frames inference as a continuous process of belief updating in which individuals navigate between differentiation and integration of information to optimize their engagement with the world. The dissertation is structured to build toward this reconceptualization. Chapters 1 and 2 establish the research context, outline the problem, articulate key questions, and detail the methodology. Chapter 3 presents a literature review on critical thinking and a phenomenographic analysis of its dominant conceptions, revealing a prevailing emphasis on logic and argumentation while also identifying alternative perspectives and critiques. Chapter 4 introduces inferential criticality as an engineered concept, arguing that inference operates as a dynamic, self-organizing system wherein criticality emerges at phase transitions—sudden shifts in system behaviour that enable adaptive and evolving inferential activity in response to an ever-changing world. A conceptual model is proposed for engaging in and observing critical inference across diverse contexts. Chapter 5 examines the pedagogical implications of this framework, slightly adapting the model from Chapter 4 to illustrate its applicability across academic disciplines. This proposed framework is then juxtaposed with a thematic analysis of syllabi from 15 undergraduate critical thinking courses across Canada, exploring how critical thinking is commonly understood, taught, and assessed. The findings reveal a strong emphasis on argument evaluation and a significant reliance on exams, tests, and quizzes as assessment methods. Chapter 6 integrates these findings, discusses broader implications, identifies limitations, and offers recommendations for future research and practice. This work challenges static, skill-based models of critical thinking, advocating for a framework grounded in active inference and self-organized criticality (SOC). Theoretical and pedagogical implications suggest that learning environments should prioritize strategies focusing on iterative differentiation and integration, contextual adaptability, and dynamic assessments that balance structure and flexibility. By integrating insights from philosophy, neuroscience, and the Scholarship of Teaching and Learning, this dissertation advances an interdisciplinary approach to understanding critical inference as a complex, embodied, and evolving process—reshaping how we conceptualize reasoning, learning, and intelligent problem-solving in classrooms and beyond.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».