Building trust with people receiving supported employment and housing first services.
Bibliographic record
Abstract
OBJECTIVES: The developing literature on supported employment for people who have a mental illness and recent history of homelessness has yet to explore the relationship between clients and their employment specialists. The objective of the present article is to explore and understand the way in which service users experience supported employment services and how these experiences differ from those receiving usual services. METHOD: Semistructured qualitative interviews were conducted with 27 people from a randomized controlled trial of supported employment, 14 receiving supported employment, and 13 receiving usual services. Thematic content analysis was used to generate themes and compare experiences between the 2 groups. RESULTS: Trust emerged as an important facilitator to development of a collaborative relationship. It developed with time and featured in the narratives of participants who found jobs. Lack of trust and communication was associated with greater difficulty finding work. People receiving usual services rarely had repeated contact with service providers and therefore did not develop working alliances to the same extent as people receiving supported employment. CONCLUSIONS AND IMPLICATIONS: Without the support of an employment specialist, participants receiving usual services relied more on internal motivation to search for employment opportunities. Programs assisting people to reach their employment goals must be sensitive to homelessness-specific experiences that may make establishing trust difficult. Vocational services should be designed to allow clients to deal exclusively with 1 service provider to permit the development of a working alliance.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".