Ethical Arguments for Providing Access to Mental Health Care through Longitudinal Relationships
Bibliographic record
Abstract
A focus on access to mental health care is critical for beneficent and just care of individuals experiencing homelessness. The delivery of this care is strengthened through building longitudinal relationships between clinicians and persons experiencing homelessness—relationships that are best understood, perhaps, through the lens of attachment theory. In this paper, we look at the prevalence of mental illness among individuals experiencing homelessness and the history of deinstitutionalization of the mentally ill. We then evaluate how three modern-day interventions—street medicine, community health clinics, and supportive housing programs—play integral roles in providing mental health care and constructing a trusting relationship. We conclude with a call for increased funding to support the expansion of these essential mental health care interventions, especially in the aftermath of COVID-19.
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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 | 0.200 | 0.312 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.080 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.026 | 0.039 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".