To Use or Not to Use the Term “Obstetric Violence”: Commentary on the Article by Swartz and Lappeman
Bibliographic record
Abstract
Based on the article by Swartz and Lappeman, we propose in this commentary to reflect on three central components linked to the concept of obstetric violence: the withdrawal of intentionality as a founding element of its recognition, the preponderant place given to the perspective of women and those affected by it, as well as the recognition of its sexist, gendered, and systemic character. We also discuss the epistemic injustice associated with obstetric violence. We stress the importance of including both health workers and health systems in the equation, even though they may be offended by the use of the term. We conclude by recalling that significant leadership must be exercised by health care workers and institutions to put an end to this form of violence.
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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 | 0.021 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.020 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.061 | 0.079 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".