Answering Huxley: an exercise in the history of examinations (1149.2)
Bibliographic record
Abstract
Twelve students in an undergraduate health sciences program, who had completed a 2nd year (sophomore) course in Anatomy and Physiology volunteered to participate in a “history” exercise. They answered two essay questions set by Thomas Henry Huxley when he was the Examiner in Physiology and Comparative Anatomy for diverse faculties at the University of London from 1857‐1870. These were selected from a question bank kindly provided by Dr. Pauline Mazumdar (University of Toronto). In preparation for the hour‐long, hand‐written exam, they studied specific sections (liver physiology, blood, vascular system) from two 19th century texts (Foster, Broussais). They later filled out a questionnaire that asked them to contrast the experience of reading older, denser texts and answering essay‐type exams with their more contemporary experiences. Many wrote thoughtful, reflective comments on the exercise that gave them an insight into the difficulties faced by students in the past (8.0 ± 1.4) that also proved to be a valuable learning experience (8.3 ± 1.2).
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 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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.055 | 0.015 |
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".