Bibliographic record
Abstract
BACKGROUND: The Maternity Experiences Survey is a project of the Canadian Perinatal Surveillance System. Its primary objective is to provide insight into Canadian women's maternity experiences. A pilot study was conducted in 2002/2003 to determine to what extent women's reports could be used to assess Canadian perinatal health policies and practices, and to test the procedures proposed for a national maternity experiences survey. METHODS: A nonrepresentative sample of 291 mothers was drawn from Canadian birth registration records. Mothers whose children had died or were no longer in their care were excluded. Participants were interviewed 9 to 11 months postpartum about prenatal, labor, and birth and postpartum experiences. RESULTS: The response rate was 86 percent. Respondents were generally comfortable answering all questions and identified areas of potential strength and weakness in the Canadian maternity care system. They had difficulty recalling information on some prenatal tests, and labor and birth procedures. The use of birth registrations to draw the pilot sample worked well. However, some regions may not be able to provide timely access to birth registrations for the purposes of a national survey. CONCLUSIONS: The high response rate and women's ability to provide information on a wide range of topics demonstrates that a national maternity survey would be an effective method of providing important maternal health information. The data collected would allow Health Canada to carry out more effective national perinatal health surveillance with a view to influencing perinatal health policy and practice.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".