“Just clearly the right thing to do”: perspectives of correctional services leaders on moving governance of health-care in custody
Bibliographic record
Abstract
PURPOSE: Governance models are a defining characteristic of health-care systems, yet little research is available about the governance of health-care delivered in correctional facilities. This study aims to explore the perspectives of correctional services leaders in British Columbia, Canada, on the motivations for transferring responsibility for health-care services in provincial correctional facilities to the Ministry of Health, as well as key lessons learned. DESIGN/METHODOLOGY/APPROACH: Eight correctional services leaders participated in one-on-one interviews between September 2019 and February 2020. The authors used inductive thematic analysis to explore key themes. To triangulate early effects of the transfer identified by participants the authors used complaints data from Prisoners' Legal Services to examine changes over time. FINDINGS: The authors identified four major themes related to the rationale for this transfer: 1) quality and equivalence of care, 2) integration and throughcare, 3) values and expertise and 4) funding and resources. Facilitators included changes in the external environment, having the right people in the right places, a strong sense of alignment and shared goals and a changing culture in corrections. Participants also highlighted challenges, including ongoing human resourcing issues, having to navigate and define shared responsibilities and adapting a large bureaucracy to the environment in corrections. Consistent with outcomes described by participants, data showed that a lower proportion of complaints received after the transfer were related to health-care. ORIGINALITY/VALUE: The perspectives of correctional leaders on the transfer of governance for health-care services in custody to the community health-care system provide novel insights into the processes and potential of this change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.023 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".