Sex-Disaggregated Systematics in Canadian Time Allocation Committee\n Telescope Proposal Reviews
Why this work is in the frame
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Bibliographic record
Abstract
Recent studies have shown that the proposal peer review processes employed by\na variety of organizations to allocate astronomical telescope time produce\noutcomes that are systematically biased depending on whether proposal's\nprincipal investigator (PI) is a man or a woman. Using Canada-France-Hawaii\nTelescope (CFHT) and Gemini Observatory proposal statistics from Canada over 10\nrecent proposal cycles, we assess whether or not the mean proposal scores\nassigned by the National Research Council's (NRC's) Canadian Time Allocation\nCommittee (CanTAC) also correlate significantly with PI sex. Classical t-tests,\nbootstrap and jackknife replications show that proposals submitted by women\nwere rated significantly worse than those submitted by men. We subdivide the\ndata in order to investigate sex-disaggregated statistics in relation to PI\ncareer stage (faculty vs. non-faculty), telescope requested, scientific review\npanel, observing semester, and the PhD year of faculty PIs. Consistent with the\nbivariate results, a multivariate regression analysis controlling for other\ncovariates confirmed that PI sex is the only significant predictor of proposal\nrating scores for the sample as a whole, although differences emerge for\nproposals submitted by faculty and non-faculty PIs. While further research is\nneeded to explain our results, it is possible that implicit social cognition is\nat work. NRC and CanTAC have taken steps to mitigate this possibility by\naltering proposal author lists in order to conceal the PI's identity among\nco-investigators. We recommend that the impact of this measure on mitigating\nbias in future observing semesters be quantitatively assessed using statistical\ntechniques such as those employed here.\n
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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 | 0.001 |
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 it