Outreach health-care services for people experiencing exclusion in high-income countries
Bibliographic record
Abstract
Inclusion health aims to prevent and address health and social inequalities for people experiencing exclusion, such as people experiencing homelessness, people who have a history of contact with the criminal justice system, people who use drugs, sex workers, vulnerable migrants, victims of modern slavery and human trafficking, and Romany Gypsy, Roma, and Travellers communities. These populations have poor health outcomes and disproportionate health inequities, partly resulting from inadequate health-care access. Outreach services can improve health-care access, but there is little evidence of how outreach operates successfully. We conducted a realist review of multicomponent outreach health-care services to understand the circumstances under which outreach works for people experiencing exclusion and why. Key components of effective outreach include person-centred services and appointments, staff expertise, high-quality communication, and close partnership with people experiencing exclusion and relevant organisations. Service users are likely to develop trust and further engage through positive experiences and regular interaction with the same staff.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".