COMPARING WOMEN'S ASSESSMENT OF MIDWIFERY AND MEDICAL CARE IN QUÉBEC, CANADA
Bibliographic record
Abstract
In 1990, the province of Québec, Canada, adopted a law that authorized the evaluation of the practice of midwifery through pilot projects before its legalization. A key objective of this evaluation, as defined by the law, was the documentation of women's assessment of maternity care, especially with regard to humanization and continuity of care. Two to 3 months after birth, 933 midwifery clients and 1,000 physicians' clients, matched on several characteristics, responded to a mailed questionnaire (response rates were 93% and 76%, respectively). Results showed that women from both groups were generally satisfied with the care they received, although women who received midwifery care were assessed as more positive on every issue surveyed. Objective measures supported impressions that were also confirmed through qualitative data analysis: midwifery clients had a greater number of and longer prenatal visits, their care was perceived to be more personalized, and a greater number of midwives' clients breastfed their infants. However, the interpretation of these results must take into account that the two groups had different personal expectations and values with regard to health and health care. These findings are enlightening in evaluating women's needs, expectations, and satisfaction with health care services and should be included in future development of maternity care, including idwifery services, in Québec and other locations.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".