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Record W4220920583 · doi:10.2105/ajph.2022.306776

Mothers Who Use Drugs: Closing the Gaps in Harm Reduction Response Amidst the Dual Epidemics of Overdose and Violence in a Canadian Urban Setting

2022· article· en· W4220920583 on OpenAlexafffundabout
Jade Boyd, Lisa Maher, Tamar Austin, Jennifer Lavalley, Thomas Kerr, Ryan McNeil

Bibliographic record

VenueAmerican Journal of Public Health · 2022
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsBritish Columbia Centre on Substance Use
FundersNational Institute on Drug AbuseCanadian Institutes of Health Research
KeywordsClosing (real estate)Harm reductionHarmMedicineEnvironmental healthPoison controlSuicide preventionHuman factors and ergonomicsInjury preventionOccupational safety and healthMedical emergencyCriminologyPsychiatryPublic healthPolitical sciencePsychologyLawNursing

Abstract

fetched live from OpenAlex

Objectives. To identify key gaps in overdose prevention interventions for mothers who use drugs and the paradoxical impact of institutional practices that can increase overdose risk in the context of punitive drug policies and a toxic drug supply. Methods. Semistructured interviews were conducted with 40 women accessing 2 women-only, low-barrier supervised consumption sites in Greater Vancouver, British Columbia, Canada, between 2017 and 2019. Our analysis drew on intersectional understandings of structural, everyday, and symbolic violence. Results. Participants’ substance use and overdose risk (e.g., injecting alone) was shaped by fear of institutional and partner scrutiny and loss (or feared loss) of child custody or reunification. Findings indicate that punitive policies and institutional practices that frame women who use drugs as unfit parents continue to negatively shape the lives of women, most significantly among Indigenous participants. Conclusions. Nonpunitive policies, including access to safe, nontoxic drug supplies, are critical first steps to decreasing women’s overdose risk alongside gender-specific and culturally informed harm-reduction responses, including community-based, peer-led initiatives to maintain parent–child relationships. (Am J Public Health. 2022;112(S2):S191–S198. https://doi.org/10.2105/AJPH.2022.306776 )

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.298
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2022
Admission routes3
Has abstractyes

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