Foucault on the Wards: Rediscovering Reflection as a Social Pediatrician in Training
Bibliographic record
Abstract
The author states that as a second-year medical student with a liberal arts degree, it was often difficult for him to reconcile his former liberal arts education with the current demands of his training. Although the medical curriculum increasingly acknowledges the importance of a biopsychosocial model, the prioritization of knowledge remains the same: know your biological, pharmacological, and anatomical facts. However, the author's experience with a social pediatrics research summer studentship moved him beyond this basic sciences mindset and provided a practical framework for the application of his liberal arts training. The experience was twofold: he worked on a research project while simultaneously shadowing a pediatrician twice a week. His project applied a Foucauldian critical discourse analysis (CDA) to an archive of texts that sought to better characterize the term social pediatrics. The author concludes that the thought-changing reflection, mentorship, and concrete clinical experiences made possible by the summer studentship expanded his worldview.The author discusses the complementary relationship between CDA, clinical experience, and self-reflection in the developing clinician. The purpose of his essay is threefold. First, by drawing on concepts from Descartes' Meditations and Plato's allegory of the cave, he establishes educational continuity between his liberal arts and medical training. Second, using clinical examples, he explores the practicality of discourse analysis and how skills regarding empathy and bias awareness are transferrable to the wards. Last, he highlights the importance of cognitive dissonance and transformative learning in the maturing physician.
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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 | 0.026 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.131 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.002 | 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".