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Record W2901873894 · doi:10.1370/afm.2314

Access to Primary Care for Persons Recently Released From Prison

2018· article· en· W2901873894 on OpenAlexaffabout
Nahla Fahmy, Fiona G. Kouyoumdjian, Jonathan Berkowitz, S. Fahmy, Carlos Magno Neves, Stephen W. Hwang, Ruth Elwood Martin

Bibliographic record

VenueThe Annals of Family Medicine · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of British Columbia HospitalMcMaster UniversitySt. Michael's HospitalUniversity of British Columbia
Fundersnot available
KeywordsPrisonMedicinePrimary careImprisonmentFamily medicinePsychiatryCriminology

Abstract

fetched live from OpenAlex

We aimed to determine if a history of recent imprisonment affects access to primary care. Using patient roles, we telephoned to request an initial appointment with all family physicians (n = 339) who were accepting new patients in British Columbia, Canada. We sequentially assigned patient scenarios: male or female recently released from prison; male or female control. Controls were 1.98 (95% CI, 1.59-2.46) times as likely to be offered an appointment compared with persons recently released from prison, with an absolute risk difference of 41.8% (95% CI, 31.0-52.5). Our study suggests discrimination is a barrier to primary care for people released from prison, even with universal health insurance. We need to improve access to primary care during the high-risk period following prison 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.457
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.299
GPT teacher head0.472
Teacher spread0.173 · 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 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

Citations50
Published2018
Admission routes2
Has abstractyes

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