Focus on Methodology: A sense of sociomaterialism: How sociomaterial perspectives might illuminate health professions education
Bibliographic record
Abstract
Emerging from the field of socio-technical studies (STS), “sociomaterial” refers to a diverse group of theoretical approaches that, broadly speaking, share a commitment to symmetrically privileging both social and material elements. Not surprisingly, the ways in which a sociomaterial researcher engages in the process of collecting and analysing data will differ from studies that foreground a more human-centered point of view. This paper introduces researchers to the principles informing sociomaterial research and demonstrates their application in the context of a problem that has reached rampant levels among healthcare professionals—burnout. In this paper, we provide an accessible, in-depth description of what we mean by the sociomaterial, describe its historical roots and elucidate what it means to engage in empirical sociomaterial work. In so doing, our goal is to illuminate the potential of sociomaterial studies for exploring the complexity of health professions education.
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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 | 0.060 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.009 | 0.107 |
| Scholarly communication | 0.021 | 0.022 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".