Housing First and harm reduction: a rapid review and document analysis of the US and Canadian open-access literature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Housing First is an evidence-based practice intended to serve chronically homeless individuals with co-occurring serious mental illness and substance use disorders. Despite housing active substance users, harm reduction is an often-overlooked element during the Housing First implementation process in real-world settings. In this paper, we explore the representation of the Housing First model within the open-access scholarly literature as a potential contributing factor for this oversight. METHODS: We conducted a rapid review of the US and Canadian open-access Housing First literature. We followed a document analysis approach, to form an interpretation of the articles' content related to our primary research questions. RESULTS: A total of 55 articles on Housing First were included in the final analysis. Only 21 of these articles (38.1%) included explicit mention of harm reduction. Of the 34 articles that did not discuss harm reduction, 22 provided a description of the Housing First model indicating it does not require abstinence from substance use; however, descriptions did not all clearly indicate abstinence was not required beyond program entry. Additional Housing First descriptions focused on the low-barrier entry criteria and/or the intervention's client-centeredness. CONCLUSIONS: Our review demonstrated a lack of both explicit mention and informed discussion of harm reduction in the Housing First literature, which is likely contributing to the Housing First research-practice gap to some degree. Future Housing First literature should accurately explain the role of harm reduction when discussing it in the context of Housing First programming, and public agencies promoting Housing First uptake should provide resources for proper implementation and monitor program fidelity to prevent model drift.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it