Systematic Variation in Reviewer Practice According to Country and Gender in the Field of Ecology and Evolution
Bibliographic record
Abstract
The characteristics of referees and the potential subsequent effects on the peer-review process are an important consideration for science since the integrity of the system depends on the appropriate evaluation of merit. In 2006, we conducted an online survey of 1334 ecologists and evolutionary biologists pertaining to the review process. Respondents were from Europe, North America and other regions of the world, with the majority from English first language countries. Women comprised a third of all respondents, consistent with their representation in the scientific academic community. Among respondents we found no correlation between the time typically taken over a review and the reported average rejection rate. On average, Europeans took longer over reviewing a manuscript than North Americans, and females took longer than males, but reviewed fewer manuscripts. Males recommended rejection of manuscripts more frequently than females, regardless of region. Hence, editors and potential authors should consider alternative sets of criteria, to what exists now, when selecting a panel of referees to potentially balance different tendencies by gender or region.
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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 | 0.145 | 0.428 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".