How Can Reflexivity Inform Critical Pedagogies? Insights from the Theory versus Practice Debate 1
Bibliographic record
Abstract
The constitutive effects of teaching activities on the study of international relations (IR) and on the practice of international relations have generated a long-term interest in approaches to teaching and learning in IR. Recently, a cluster of literature has emerged that focuses on critical pedagogy in IR, which questions traditional relations of power, ideas, and norms in the classroom. However, these inquiries have yet to be systematically connected with reflexivity in IR (i.e., the developing awareness of the diversity, production, and positionality of knowledge). This article proposes that critical pedagogies and reflexivity are mutually reinforcing. It argues that applying reflexivity to teaching activities in IR raises awareness about the social conditions enabling the (re)production of specific understandings of the world. To support this proposition, the article presents and evaluates a trial IR seminar inspired by reflexivity. In this trial seminar, three aspects of reflexivity were developed (i.e., theoretical, sociological, and self-reflexivity), each of which supports critical pedagogy. This article explains how these three perspectives were infused into different trial seminar activities, to varying degrees of success. It also evaluates how the development of the reflexive agenda can be of particular benefit to IR scholars, IR students, and critical pedagogy as a whole.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.090 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.010 | 0.168 |
| Scholarly communication | 0.032 | 0.042 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".