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Record W4412592726 · doi:10.1177/10901981251345407

Addressing Criminal Legal System Health Inequities Through Redirection

2025· article· en· W4412592726 on OpenAlexaff
Noah Painter‐Davis, Janet Page‐Reeves, Matthew E. Borrego, Theresa H. Cruz, Sarah Leiter, Kimberly R. Huyser, Linda Freeman

Bibliographic record

VenueHealth Education & Behavior · 2025
Typearticle
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsUniversity of British Columbia
FundersNational Institute on Minority Health and Health DisparitiesWilliam T. Grant Foundation
KeywordsHealth equityEquity (law)Public relationsPublic healthFocus groupPolitical scienceEthnic groupSocial determinants of healthSociologyMedicineNursingLaw

Abstract

fetched live from OpenAlex

The criminal legal system and youth delinquent systems (CL/DS) are increasingly recognized as a primary sources of racial/ethnic inequity (REI) in health. Research funding institutions are beginning to focus on the CL/DS as a social determinant of health, some CL/DS officials are centering equity as a core concern, and some problematic CL/DS practices are being rolled back. However, the impact of such efforts may be limited because they typically focus on the most visible manifestations of inequity but often fail to address root causes and complex system dynamics. More meaningfully reducing CL/DS-linked health inequities requires a better understanding of their complexity and barriers to change. Preparatory work is needed to develop appropriate information, communication strategies, and collaborative partnerships. To support these arguments, we offer an evaluation of our ongoing qualitative and quantitative research in New Mexico, which focuses on practices that redirect individuals from typical CL/DS practices in ways that minimize CL/DS involvement and its consequences. We review the sources of REI in CL/DS redirection practices, discuss how increased collaboration between public health and public safety agencies may impact REI, describe how differences in values, priorities, and strategies toward issues of equity pose barriers to REI reduction efforts, and discuss important building blocks for reducing siloing and working toward greater health equity through redirection from the CL/DS.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
Scholarly communication0.0000.001
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 head0.268
GPT teacher head0.580
Teacher spread0.312 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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