Barriers to obtaining employment for people with severe mental illness experiencing homelessness
Bibliographic record
Abstract
BACKGROUND: The rate of unemployment among homeless people is estimated to exceed 80%. A high prevalence of mental illness partially explains this figure, but few studies about the relationship between employment and homelessness have focused on homeless people with mental illness. AIM: The present study explores the self-reported barriers to employment in a sample of individuals with mental illness when they were homeless. METHODS: A sample of 27 individuals with mental illness and recent experiences of homelessness, who had expressed an interest in working, participated in semi-structured qualitative interviews. Inductive analysis was used to identify barriers to employment. FINDINGS: The prominent barriers include: (1) current substance abuse, (2) having a criminal record, (3) work-impeding shelter practices, and (4) difficulties obtaining adequate psychiatric care. CONCLUSION: Individuals who have been homeless and have a mental illness report facing specific barriers associated with mental illness, homelessness, or the interaction between the two. Additional research should explore how supported housing and employment interventions can be tailored to effectively serve this group.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".