Always, already-medicalized: Women’s prenatal knowledge and choice in two Canadian contexts
Bibliographic record
Abstract
Women’s childbirth choices occur within contested discourses about medical, natural, and woman-centered births. All three perspectives, to slightly differing degrees, presume an autonomous female subject who makes childbirth choices. Thus informed choice is posed as a crucial corrective to the increasing medicalization of childbirth. This article employs a critical feminist analysis to examine how women learn about childbirth and make choices long before the moment of informed choice. Interviews with 40 pregnant and recently birthing women in two cities in Alberta, Canada illustrate how media, family and friends, and prenatal courses comprised core pre-birth knowledge systems informing women’s decision-making. The interviews exposed how medicalization is naturalized in these knowledge systems, so that women approached their actual births with an already-medicalized set of perceptions. This already-medicalized knowledge foreclosed women’s choices, a finding that complicates arguments over improving informed choice during childbirth as a means of reducing childbirth medicalization.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.047 | 0.024 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| 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".