EVOLUTION OF A SCIENTIFIC MEETING: EIGHTY ANNUAL MEETINGS OF THE AMERICAN SOCIETY OF MAMMALOGISTS, 1919–2000
Bibliographic record
Abstract
Abstract The American Society of Mammalogists has held 80 annual meetings between 1919 and 2000. These meetings have been held in 32 states, the District of Columbia, Canada, and Mexico. At least 86 people have served as the chair or co-chair of the Local Committee planning the meetings. The number of technical presentations has grown from a low of 17 in 1921 to 340 in 1994. Symposia were an early feature of annual meetings but did not become a regular feature until 1971. Poster presentations were introduced in 1979 and reached a high of 195 posters at the 1994 annual meeting. Two trends are evident in the analyses of presentation data from annual meetings. There has been a major increase in the number of presentations, especially since 1968, when the number of presentations first exceeded 100. The other trend is the significant increase of participation of women scientists in the annual meetings of the Society. This trend had its origins in the late 1960s and was significantly aided by the addition of poster sessions, which have been popular venues for women scientists to present their research results. However, women are not as well represented as organizers or invited participants in symposia.
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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.008 |
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".