Understanding the social determinants of substance use among pregnant-involved young Aboriginal women : a mixed methods research project
Bibliographic record
Abstract
There is a lack of research exploring the social, political and historical contexts of substance use during pregnancy among young Aboriginal women. Although Aboriginal women have been hyper-visible in policies and programming for substance use during pregnancy in Canada, there remains a dearth of information about Aboriginal women’s experiences with substance use and pregnancy in the published literature. In order to understand the social determinants of substance use during pregnancy from the perspective of young Aboriginal women themselves, a convergent mixed methods research project was conducted. The research project included a secondary data analysis (N=291), life history interviews (N=24), and an innovative pilot participant-generated mapping exercise called CIRCLES (Charting Intersectional Relationships in the Context of Life Experiences with Substances) developed by the author (N=17). The research project’s findings were integrated to inform the creation of a new wellness-focused model of the social determinants of substance use among pregnant-involved young Aboriginal women. The new model identifies several points of intervention for supporting women’s strengths, resilience and the maintenance of the mother-child unit to promote wellness among women. Further research is needed to test this new model among larger populations, and to identify specific resiliency factors to support Aboriginal mothers and their children.
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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 | 0.024 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".