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Record W2292946397 · doi:10.1186/s13104-016-1935-4

Access to primary care in adults in a provincial correctional facility in Ontario

2016· article· en· W2292946397 on OpenAlexafffundabout
Samantha Green, Jessica Foran, Fiona G. Kouyoumdjian

Bibliographic record

VenueBMC Research Notes · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsMcMaster UniversitySt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsMedicineEmergency departmentPrimary careFamily medicinePopulationHealth careNursingEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about access to primary care either prior to or following incarceration in Canada. International data demonstrate that the health of people in prisons and jails is poor, and access to primary care in the community may be inadequate for incarcerated persons. We aimed to describe the primary care experience of adults in custody in a provincial correctional facility in Ontario in the 12 months prior to admission. METHODS: We conducted a written survey, and invited all persons in the institution to participate, excluding those in segregation. RESULTS: One hundred and twenty-five persons participated, 16.8% of whom were women. The median age was 33. In the 12 months prior to admission to custody, 32.2% (95% CI 23.5-40.8%) of respondents did not have a family doctor or other primary care provider and 48.2% (95% CI 38.8-57.6%) had unmet health needs. Participants reported a mean of 2.1 (SD = 2.8) emergency department visits in the 12 months prior to admission. CONCLUSIONS: Study participants report a lack of access to primary care, a high mean number of emergency department visits, and high unmet health care needs in the 12 months prior to incarceration. Time in custody may present an opportunity for connecting this population with primary care and improving health.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.149
GPT teacher head0.426
Teacher spread0.277 · 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 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

Citations27
Published2016
Admission routes3
Has abstractyes

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