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Record W6887697788 · doi:10.17605/osf.io/bt7q8

Exploring the Mental Health Journeys of Women on Probation and Parole in Canada: Symptoms and Psychological Service Utilization

2024· other· en· W6887697788 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthEthnic groupMental health serviceIndigenousSuicide preventionService (business)Qualitative researchHuman factors and ergonomics

Abstract

fetched live from OpenAlex

Over the past decade, the number of women sentenced federally in Canada has increased by 20%. Despite this rising number, little is known about the mental health experiences of women under community supervision, including those who are mothers and/or identify as Indigenous or as ethnic or racial minorities. A convergent mixed-methods approach will be used to investigate the mental health journeys of women on probation and parole across Canada. The objectives of the present study are 1) to determine the prevalence of anxiety, depression, and posttraumatic stress symptoms within this population, and to assess whether the prevalence of these symptoms differs by parental status; and 2) to explore this population’s psychological service use experiences. Participants will be recruited through criminal legal agencies and community organizations across Canada. Quantitative and qualitative data will be collected through an online survey in Qualtrics. Results will inform the creation of psychological services tailored to the mental health needs and preferences of women on probation and parole in Canada.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.190
GPT teacher head0.358
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2024
Admission routes1
Has abstractyes

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