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Record W4399425918 · doi:10.14738/assrj.115.17008

Amadeusz’s Prosper: Effective Reintegration of Adults Facing Firearm-Related Charges in Ontario, Canada

2024· article· en· W4399425918 on OpenAlexaffabout
Ardavan Eizadirad, Tina Nadia Chambers, Sheena Blake Brown

Bibliographic record

VenueAdvances in Social Sciences Research Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGun Ownership and Violence Research
Canadian institutionsHumber PolytechnicWilfrid Laurier University
Fundersnot available
KeywordsRecidivismCommunity integrationPsychologyIntersectionalityCriminologyPolitical sciencePublic relationsSociologyMedical educationGender studiesMedicine

Abstract

fetched live from OpenAlex

This study evaluates the impact of Amadeusz’ Prosper program which supports individuals with firearm-related charges between the ages of 18 to 29 in Ontario, Canada. Prosper offers intensive case management through caseworkers who co-create tailored support plans with participants based on their immediate needs and long-term goals. The program supports individuals during incarceration and post-release once back in community. This study engaged 44 participants through interviews conducted between October 2022 and April 2023. Participants included program beneficiaries (n=29), family members (n=8), community partners (n=4), and caseworkers (n=3). Intersectionality and Critical Race Theory paradigms were applied as part of data analysis to uncover the program's impact, strengths, and barriers in implementation. Results showed a correlation between the program and positive outcomes in personal development, well-being, and reintegration of participants. Overall, the study contributes to filling in the research gap offering nuanced insights into how to support individuals with firearm-related charges in Canada as part of offering more effective reintegration supports and reducing recidivism.

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)0.012
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.002
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 head0.049
GPT teacher head0.449
Teacher spread0.400 · 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.

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

Citations0
Published2024
Admission routes2
Has abstractyes

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