MétaCan
Menu
Back to cohort
Record W6906471500 · doi:10.17605/osf.io/pv5hs

Psychological Barriers Women Experience During Reintegration After Incarceration

2024· other· en· W6906471500 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPrisonPopulationProsocial behaviorCoping (psychology)Mental illnessSubstance useRecidivismCriminal justice

Abstract

fetched live from OpenAlex

As the fastest-growing prison population worldwide, women face distinct barriers to successful community reintegration after incarceration. In Canada, the number of females sentenced to federal institutions has increased by over 44% for non-Indigenous women and 76.4% for Indigenous women between 2006 and 2016, a substantially higher proportion than males (Department of Justice, 2018). Mental and emotional wellness is substantially impacted by social inequalities and gender disparities that women experience at significantly higher rates than males, such as abuse, poverty, systemic oppression, and substance use (Nicholls et al., 2009; Yu, 2018). Transitioning from incarceration to the community can initiate a phase of emotional turmoil due to the need to adapt quickly and learn from others (Pettus-Davis & Kennedy, 2019). With a higher likelihood of women experiencing victimization and social inequalities compared to men, there is a substantial overlap in women’s negative coping strategies (e.g., substance use, self-harm) and involvement with the legal system (Canadian Women’s Foundation, 2014). Despite having established goals, risk management strategies, and regulations that may be in place for individuals leaving incarceration, women often enter the community in survival mode, acutely aware of the need to quickly create a vastly different lifestyle to live a law-abiding life (Tyagi, 2016). With 59% of females reoffending within six months after incarceration (a higher proportion than males), identifying women’s needs and barriers to support their success in a prosocial life upon release could be foundational to developing needed change in ending the cycle of reincarceration (Department of Justice, 2020). Despite having unique pathways to criminal behaviour and being the fastest-growing population to commit crimes, gender-responsive research is lacking (Yu, 2018). While risk assessment tools speak to the likelihood of future criminal behaviour based on the individual or past behaviour, the barriers women experience when making decisions at such a critical juncture are essential to understand to prevent the cyclical nature of incarceration. By determining and understanding the psychological barriers women experience, such as stigma, loneliness, and self-esteem issues, we can contribute to a positive reintegration upon prison re-entry in the future by targeting and focusing on addressing those barriers upon release. Through conducting surveys and semi-structured interviews with women who have previously been incarcerated in a Canadian Correctional Facility, this study examined how psychological barriers may impact women’s reintegration after incarceration. Within the surveys, participants responded to questionnaires on specific psychological factors, whereas during the interviews, women will be provided the opportunity to share their experiences, advice, and perspectives about reintegration after incarceration. If the findings of this study indicate an association between specific psychological barriers with women’s community connectedness and prosocial reintegration, a need for further resources and inclusive services may be suggested to contribute to a decrease in recidivism upon release.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.355
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0040.001
Open science0.0040.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0360.023

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 head0.021
GPT teacher head0.376
Teacher spread0.355 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Explore more

Same venueOpen Science FrameworkFrench-language works237,207