Joint ESCMID, FEMS, IDSA, ISID and SSI position paper on the fair handling of career breaks among physicians and scientists when assessing eligibility for early-career awards
Bibliographic record
Abstract
BACKGROUND: Though women increasingly make up the majority of medical-school and other science graduates, they remain a minority in academic biomedical settings, where they are less likely to hold leadership positions or be awarded research funding. A major factor is the career breaks that women disproportionately take to see to familial duties. They experience a related, but overlooked, hurdle upon their return: they are often too old to be eligible for 'early-career researcher' grants and 'career-development' awards, which are stepping stones to leadership positions in many institutions and which determine the demographics of their hierarchies for decades to come. Though age limits are imposed to protect young applicants from more experienced seniors, they have an unintended side effect of excluding returning workers, still disproportionately women, from the running. METHODS: In this joint effort by the European Society of Clinical Microbiology and Infectious Diseases, the Federation of European Microbiological Societies, the Infectious Disease Society of America, the International Society for Infectious Diseases and the Swiss Society for Infectious Diseases, we invited all European Congress of Clinical Microbiology and Infectious Diseases-affiliated medical societies and funding bodies to participate in a survey on current 'early-career' application restrictions and measures taken to provide protections for career breaks. RECOMMENDATIONS: The following simple consensus recommendations are geared to funding bodies, academic societies and other organizations for the fair handling of eligibility for early-career awards: 1. Apply a professional, not physiological, age limit to applicants. 2. State clearly in the award announcement that career breaks will be factored into applicants' evaluations such that: • Time absent is time extended: for every full-time equivalent of career break taken, the same full-time equivalent will be extended to the professional age limit. • Opportunity costs will also be taken into account: people who take career breaks risk additional opportunity costs, with work that they did before the career break often being forgotten or poorly documented, particularly in bibliometric accounting. Although there is no standardized metric to measure additional opportunity costs, organizations should (a) keep in mind their existence when judging applicants' submissions, and (b) note clearly in the award announcement that opportunity costs of career breaks are also taken into account. 3. State clearly that further considerations can be undertaken, using more individualized criteria that are specific to the applicant population and the award in question. The working group welcomes feedback so that these recommendations can be improved and updated as needed.
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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 | 0.209 | 0.246 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.011 | 0.011 |
| Research integrity | 0.024 | 0.016 |
| Insufficient payload (model declined to judge) | 0.015 | 0.014 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".