Met and unmet needs of homeless individuals at different stages of housing reintegration: A mixed-method investigation
Bibliographic record
Abstract
This study aimed to identify and compare major areas of met and unmet needs reported by 455 homeless or recently housed individuals recruited from emergency shelters, temporary housing, and permanent housing in Quebec (Canada). Mixed methods, guided by the Maslow framework, were used. Basic needs were the strongest needs category identified, followed by health and social services (an emergent category), and safety; very few participants expressed needs in the higher-order categories of love and belonging, self-esteem, and self-actualization. The only significant differences between the three housing groups occurred in basic needs met, which favored permanent housing residents. Safety was the only category where individuals reported more unmet than met needs. The study results suggested that increased overall access to and continuity of care with family physicians, MD or SUD clinicians and community organizations for social integration should be provided to help better these individuals. Case management, stigma prevention, supported employment programs, peer support and day centers should particularly be more widely implemented as interventions that may promote a higher incidence of met needs in specific needs categories.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".