Setting the standard: <i>Medical Education</i> 's first 50 years
Bibliographic record
Abstract
CONTEXT: By understanding its history, the medical education community gains insight into why it thinks and acts as it does. This piece provides a Foucauldian archaeological critical discourse analysis (CDA) of the journal Medical Education on the publication of its 50th Volume. This analysis draws upon critical social science perspectives to allow the examination of unstated assumptions that underpin and shape educational tools and practices. METHODS: A Foucauldian form of CDA was utilised to examine the journal over its first half-century. This approach emphasises the importance of language, and the ways in which words used affect and are affected by educational practices and priorities. An iterative methodology was used to organise the very large dataset (12,000 articles). A distilled dataset, within which particular focus was placed on the editorial pieces in the journal, was analysed. RESULTS: A major finding was the diversity of the journal as a site that has permitted multiple - and sometimes contradictory - discursive trends to emerge. One particularly dominant discursive tension across the time span of the journal is that between a persistent drive for standardisation and a continued questioning of the desirability of standardisation. This tension was traced across three prominent areas of focus in the journal: objectivity and the nature of medical education knowledge; universality and local contexts, and the place of medical education between academia and the community. CONCLUSIONS: The journal has provided the medical education community with a place in which to both discuss practical pedagogical concerns and ponder conceptual and social issues affecting the medical education community. This dual nature of the journal brings together educators and researchers; it also gives particular focus to a major and rarely cited tension in medical education between the quest for objective standards and the limitations of standard measures.
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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 | 0.023 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.031 | 0.020 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".