Bibliographic record
Abstract
The concept of ‘‘the hidden curriculum’’ has become a part of the everyday discourse of medical education. With roots in the broader field of education, the concept has had a significant influence on medical education since Hafferty & Franks brought it to our attention (1994). Twenty years later, this personal view paper problematizes the concept and discusses whether ‘‘the hidden curriculum’’ is a concept that has run its course. Reflecting on my experience at a recent medical education conference, I realize that perhaps the most striking learning experience for me was, as they often are, an informal one. Time and time again, I heard conference delegates use phrases like: What can you do? It’s the hidden curriculum in action. Oh, it’s probably because of the hidden curriculum. That’s bad! Talk about hidden curriculum! ‘‘The hidden curriculum’’ rolled off the tongues of medical educators from across the country: established and emerging, clinical and non-clinical. It was referred to in plenary sessions as well as in countless oral and poster presentations. The hidden curriculum was such a prevalent discourse of my conference experience that I found myself thinking about it conceptually. As a recent convert to the power of social media for
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.006 |
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; both teacher heads agree on what is shown here.
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".