Bibliographic record
Abstract
The central question that guides this article is: how should we think critically about our responsiveness to human suffering? This question is important because, as Butler (2010) noted, humanity is split into two groups: those whose lives evoke an immediate concern from us, and those whose suffering or deaths fail to move us. First, I present a brief overview of critical thinking pedagogy. Then, I discuss critical thinking’s affinity with rationalism and “logicism,” i.e. good thinking is logical thinking. I make an argument that critical thinking pedagogy with an excessively rationalistic bent may not enable us to respond ethically to the suffering of self and others. To counterbalance critical thinking’s over-reliance on rationalism, I discuss what we can learn from the recent literature on critical studies of emotion or the “affective turn.” I present four pedagogical principles that I hope will provide practical implications for taking an affective approach to critical thinking pedagogy. I conclude the article with an example of a critical-affective frame analysis that can be applied to critical thinking pedagogy in diverse classroom settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".