A Snapshot of Pulmonary Medicine at the Turn of the Century: The American Thoracic Society Membership
Bibliographic record
Abstract
To describe the characteristics of the American Thoracic Society, the Membership Committee developed a survey to assess demographics, training, professional activities, and needs of a diverse membership with a growing international segment. It also provided an opportunity to determine how the Society reflects the current state of pulmonary medicine in the United States. A self-administered survey was mailed to active members. Of responding members, 80% reside in the United States or Canada; the remainder come from 90 different countries. The majority of North American respondents (79%) were white, non-Hispanic. Seventeen percent of respondents were female. Female respondents were younger, with a mean age of 42 years, compared with 47 years for males. Sixty-five percent of respondents identified clinical practice, 20% research, and 5% teaching as their major activity. More women (33%) than men (22%) identified themselves as researchers. The majority of respondents (69%) have a medical school faculty affiliation. The American Thoracic Society represents a global organization with diverse clinical expertise and scientific interests. The majority of respondents are clinicians; however, the membership has a strong academic bent with most reporting academic affiliation, and describing teaching as a secondary activity.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".