Examining the impact of naming equity within perinatal substance use and mental health policy: a scoping review
Bibliographic record
Abstract
The ways in which we understand and respond to perinatal substance use are explicitly and implicitly driven by policy. Perinatal substance use is a visible manifestation of intersecting systems of oppression, shaped by racist, colonial and sexist discourses surrounding mothering and drug use. Policies related to perinatal substance use and mental health have far-reaching impacts on families, communities and generations. This scoping review examined the conceptualization and operationalization of equity within foundational perinatal policies in one Canadian province, British Columbia (BC), between 2005 and 2025. Documents were included if they were: (1) provincial-level policy documents that either (a) guided perinatal service delivery generally or (b) focused on mental health promotion, prevention of mental disorders or harms of substance use; (2) publicly available; and (3) published within the study timeframe. Inductive content analysis and sensitizing questions were used to explore how equity concepts were conceptualized and integrated. In total, 30 documents met inclusion criteria. Equity was mentioned in 15, but only 4 provided explicit definitions. Often, implied proxy terms for equity were substituted to discuss equity considerations, such as risk, disadvantage, social determinants of health, vulnerable, marginalized and harm reduction, with limited direction on public health system roles or accountability in addressing root causes of inequities. Content analysis yielded the following missed opportunities in the results: an absence of clear definitions; focus on accessibility; inattention to structural conditions; and incoherent concepts of equity. Given BC's reputation as a leader in equity-oriented perinatal substance use policy, these gaps are notable. In the context of an expanding drug poisoning crisis and increasing global recognition of equity as foundational to public health, it is imperative to examine how equity is understood and actioned in policy to strengthen alignment between intentions and outcomes.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.065 | 0.237 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.035 | 0.041 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".