Paul B. Beeson Career Development Awards in Aging Research and U.S. Medical Schools Aging and Geriatric Medicine Programs
Bibliographic record
Abstract
Established in 1995, the Paul B. Beeson Career Development program provides faculty development awards to outstanding junior and midcareer faculty committed to academic careers in aging-related research, training, and practice. This study evaluated the effect of 134 Beeson Scholars on their medical schools' aging and geriatric medicine programs and on the field of aging research from 1995 to 2007. Quantitative and qualitative survey data from multiple sources, including the American Geriatrics Society/Association of Directors of Geriatric Academic Programs' Geriatrics Workforce Policy Studies Center, National Institutes of Health (NIH) rankings of research funding, and other governmental databases were used to compare 36 medical schools with Beeson Scholars with 34 similar medical schools without Beeson scholars and to examine the influence of Beeson Scholars on the field of geriatrics and aging. Most Beeson Scholars remained at the institution where they trained during their Beeson award, and 89% are still practicing or conducting research in the field of geriatrics and aging. Twenty-six (19.4%) of the scholars have led institutional research mentoring awards, 51 (39%) report leadership roles in institutional program project grants, and 13 (10%) report leadership roles in the Clinical and Translational Science Award programs at their institutions. Beeson Scholars are more likely than a matched sample of non-Beeson NIH K awardees to study important geriatric syndromes such as falls, cognitive impairment, adverse drug events, osteoporosis, and functional recovery from illness. Total Beeson Impact Years (the total number of years all Beeson Scholars have worked at each school) is positively correlated with more geriatrics research faculty, after controlling for NIH funding rank (P=.02). Beeson Scholars have made positive contributions to the development of academic geriatrics research programs at U.S. medical schools.
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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 | 0.010 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".