The Presentation of Complementary and Alternative Medicine Information in Canadian Midwifery Care
Bibliographic record
Abstract
This paper uses discourse analysis to consider midwives’ and pregnant women’s discussions of conventional and complementary and alternative medicine interventions for inducing labour. Participants distinguished between “natural” and “medical” methods and used information sources based on both biomedical evidence and women’s experience to justify and challenge authority claims.Cet article utilise l’analyse du discours pour examiner les conversations des sages-femmes et des femmes enceintes au sujet des interventions en médecine traditionnelle, douce et alternative pour assister l’accouchement. Les participantes ont fait la distinction entre les méthodes « naturelles » et « médicales » et ont utilisé des sources d’information basées aussi bien sur les évidences biomédicales que sur l’expérience de femme pour justifier et remettre en question les autorités concernées.
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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 | 0.017 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.030 | 0.021 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 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".