Women in clinical trials: a review of policy development and health equity in the Canadian context
Bibliographic record
Abstract
Health equity in pharmaceutical research is concerned with creating equal opportunities for men and women to partake in clinical trials. Equitable representation is imperative for determining the safety, effectiveness, and tolerance of drugs for all consumers. Historically, women have been excluded from participating in clinical research leading to a lack of knowledge regarding drug effects and their consequences. This paper examines the changes made since the implementation of Canadian policies on the representation of women in clinical trials, the analysis of sex and gender, as well as the discourses that are prominent among researchers. A feminist ethics framework is used to examine the structures that endeavor to elucidate women's involvement in trials, as experienced under extensive patriarchal history. Scholarly literature and Canadian government policy documents are used to explore the development of clinical trials as pertaining to sex and gender. Findings suggest that women continue to be underrepresented or excluded from important research, highlighting ongoing ethical and justice concerns. Improvement recommendations for policies are outlined.
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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 | 0.029 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.009 | 0.024 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".