Academic criteria for promotion and tenure in faculties of biomedical sciences: a cross-sectional analysis of 146 universities
Bibliographic record
Abstract
ABSTRACT Objectives To determine the presence of a set of pre-specified traditional and progressive criteria used to assess scientists for promotion and tenure in faculties of biomedical sciences among universities worldwide. Design Cross-sectional study. Setting Not applicable. Participants 170 randomly selected universities from the Leiden Ranking of world universities list were considered. Main outcome measures Two independent reviewers searched for all guidelines applied when assessing scientists for promotion and tenure for institutions with biomedical faculties. Where faculty-level guidelines were not available, institution-level guidelines were sought. Available documents were reviewed and the presence of 5 traditional (e.g., number of publications) and 7 progressive (e.g., data sharing) criteria was noted in guidelines for assessing assistant professors, associate professors, professors, and the granting of tenure. Results A total of 146 institutions had faculties of biomedical sciences with 92 having eligible guidelines available to review. Traditional criteria were more commonly reported than progressive criteria (t(82)= 15.1, p= .001). Traditional criteria mentioned peer-reviewed publications, authorship order, journal impact, grant funding, and national or international reputation in 95%, 37%, 28%, 67%, and 48% of the guidelines, respectively. Conversely, among progressive criteria only citations (any mention in 26%) and accommodations for extenuating circumstances (37%) were relatively commonly mentioned; while there was rare mention of alternative metrics for sharing research (2%) and data sharing (1%), and 3 criteria (publishing in open access mediums, registering research, and adhering to reporting guidelines) were not found in any institution reviewed. We observed notable differences across continents on whether guidelines are accessible or not (Australia 100%, North America 97%, Europe 50%, Asia 58%, South America 17%), and more subtle differences on the use of specific criteria. Conclusions This study demonstrates that the current evaluation of scientists emphasizes traditional criteria as opposed to progressive criteria. This may reinforce research practices that are known to be problematic while insufficiently supporting the conduct of better-quality research and open science. Institutions should consider incentivizing progressive criteria. Registration Open Science Framework ( https://osf.io/26ucp/ ) What is already known on this topic Academics tailor their research practices based on the evaluation criteria applied within their academic institution. Ensuring that biomedical researchers are incentivized by adhering to best practice guidelines for research is essential given the clinical implications of this work. While changes to the criteria used to assess professors and confer tenure have been recommended, a systematic assessment of promotion and tenure criteria being applied worldwide has not been conducted. What this study adds Across countries, university guidelines focus on rewarding traditional research criteria (peer-reviewed publications, authorship order, journal impact, grant funding, and national or international reputation). The minimum requirements for promotion and tenure criteria are predominantly objective in nature, although several of them are inadequate measures to assess the impact of researchers. Developing and evaluating more appropriate, progressive indicators of research may facilitate changes in the evaluation practices for rewarding researchers.
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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 | 0.017 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".