Victimized or Validated? Responses to Substance-Using Pregnant Women
Bibliographic record
Abstract
Les femmes qui utilisent des substances noci~esdurantleur~rossessesontsouuent stigrnatise'es et juge'es par le discours public, On a l'impression que c'est h sante ' et les droits du foetus qui sont primordiaux, et non h sante ' de h femrne. Les auteures pre'conisent une politique et un traitement qui valident B lafois lasante'dela md.reetdel'enfant Substance use among pregnant women is a major public health prob-lem in Canada. Some studies esti-mate that approximately 20-30 per cent of pregnant women in Canada and the United States use tobacco (Coleman and Joyce; Connor and McIntyre), with one study estimat-ing tobacco use as low as eleven per cent (Health Canada 2002). Data suggest that the rate of smoking dur-ing pregnancy varies greatly with the age of the woman. In a 1998-1999 survey of mothers with children un-der two years of age, 53 per cent of mothers under 20 years of age had smoked during pregnancy, compared to 12 per cent of mothers aged 35 years or older (Health Canada2003). Approximately ten per cent (9.6 per cent) of Canadian women who were pregnant at the time ofthe 200 1 Canadian Community Health Sur-vey indicated they drankalcohol dur-ing thepast week (compared to 44.5 per cent of women who were not pregnant).Over 14 per cent ofmoth-ers indicated that they drank alcohol
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".