Bibliographic record
Abstract
15.1 full-time and 4.1 part-time faculty, 9.4 of whom are tenured 73 medical students, 12.2 graduate students, 7.5 postdoctoral fellows, and 4.5 administrative support staff 1.4 unfilled, full-time faculty positions salaries ranging from an average low of $37,764 for instructors to an average high of $122,375 for professors 41.8% of departmental income derived from extramural research institutional funding (2001–2002) of $1,443,143 11,870.4 sq. ft., excluding teaching space. Determine whether there are enough, too many, or too few future anatomists in the training pipeline to meet teaching needs in the coming years; Provide department chairs with benchmarking data to compare departmental funding, salaries, and infrastructure support with other schools in the United States and Canada; Provide information to assess graduate research and training programs in comparison with others. The impetus for this survey stemmed in part from reports that medical school administrators' plans for faculty hiring and curriculum changes are based on the supposition that too few anatomists are being trained to meet future teaching needs. A key goal of the survey was to gather the data to support or refute this assertion, which could then lead to the development of strategies for the future. The AAA's reading of the data from the 95 chairs who responded shows that we seem to be training enough anatomists to meet future teaching needs—but, for a variety of reasons, many of those who are trained do not subsequently teach. This issue was addressed in a February 2003 session at the AACBNC annual meeting and reported on in the March 2003 AAMC Reporter (reprinted in the AAA Newsletter, June 2003, page 5). The AAA is planning follow-up meetings this fall with other anatomy organizations. Because this was a first-time survey, we have no trends to report. The data can only be compared to what is “known” intuitively or found in other sources. Based on the feedback and interest of those who view the data, we expect to revise the survey as needed and repeat it periodically. Faculty Data Salary & Funding Data Infrastructure Training by Subject Teaching Gross Anatomy Verbatim Responses to questions such as: • You indicated that you anticipate great or moderate difficulty in finding people to teach Gross Anatomy. How do you plan to fill vacancies in this field? • What type of incentives does the institution provide for department faculty to augment their salaries from grant funds? To comment or request a more complete data compilation (available to members only), please send an E-mail to AAA at exec@anatomy.org.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".