Promoting replicable sexual science: A methodological review and call for metascience
Bibliographic record
Abstract
Concerns have increased within the medical and social science communities about the replicability of scientific findings, and subsequently, assessments of replicability and proposals for how it may be increased have become more common. Sexual scientists, however, with few exceptions, have yet to formally participate in the published discourses about replicability. In this commentary, I begin by highlighting how replicability is important for science in general, and then arguing that sexual science could be uniquely and negatively impacted without more direct involvement in the replicability movement from those within our field. I then briefly review several mechanisms through which replicability can be undermined in research, and some of the proposals for addressing these issues. I conclude by offering some ideas for how sexual scientists might begin to evaluate and improve the replicability of our field, and stress the need for sexual scientists to add their voices to the ongoing discussions about the problem of replicability of scientific findings.
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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 | 0.585 | 0.761 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.019 | 0.022 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.017 | 0.030 |
| Open science | 0.011 | 0.010 |
| Research integrity | 0.019 | 0.019 |
| 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; 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".