Not wanted in the study: an ethical, medical and political analysis of the exclusion of pregnant women from clinical research studies
Bibliographic record
Abstract
Review and analysis of current clinical research practice suggests a general trend towards excluding pregnant women from clinical research studies. Although exclusionary research practices are premised upon concerns for the well-being of the fetus and the pregnant women, such practices can also produce various inadvertent harms to both parties. In particular, exclusion of pregnant women from clinical research limits the quality of care provided to pregnant women by impeding individual access to innovative research protocols and by limiting data collection applicable to the pregnant population. A review and analysis of relevant historical, legal, ethical, clinical, scientific and political documents suggests that various changes should be made to current clinical practice. To produce many such changes there is a need for a comprehensive, progressive Canadian health policy to be used to guide and direct researchers and research ethics boards in the appropriate inclusion of pregnant women in clinical research studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.472 | 0.427 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.022 | 0.068 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.014 | 0.024 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".