Bibliographic record
Abstract
T he photo gallery on the following pages is a nod to the discussion about the 'wall of men' in Omnia.This portrait gallery opposite the Faculty Club is made up exclusively of men.That can be explained by the dearth of professional portraits of WUR women.But we do have photos of them.Who belongs in a women's hall of fame, then?Any selection is somewhat arbitrary.The men's hall of fame includes rectors and professors, renowned or otherwise, from WUR's early history.But there hasn't been a female rector yet, and WUR's early history didn't feature any women in the highest academic echelons.The first woman professor in Wageningen only appeared on the scene in 1952, 34 years after the founding of the National Agricultural College.The honour went to professor of Agricultural Home Economics Mien Visser.As president of the Dutch Association of Rural Women, Visser helped develop an academic course in Domestic Science at Wageningen.A year later, she also became the new degree programme's first professor, a position she held for almost a quarter of a century until her sudden death in 1977.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.250 | 0.023 |
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".