Soins intégrés auprès des personnes LGBTQI+ migrantes : la place des soins psychosociaux
Bibliographic record
Abstract
INTRODUCTION: LGBTQI+ migrants are at greater risk of facing health issues, including mental health issues, especially since the arrival of COVID-19. Furthermore, they face many barriers to accessing care in Quebec. It is in this context that Clinic Mauve was implemented, which aims to remove these barriers by offering medical and psychosocial care in an integrated care setting to LGBTQI+ migrants in Montreal. PURPOSE OF RESEARCH: The purpose of this article is to identify the benefits and challenges of a model like the Clinic Mauve in addressing the psychosocial needs of LGBTQI+ migrant individuals. RESULTS: The analysis shows that the Clinic Mauve model, because of its approaches is able to remove some of the barriers to accessing care for LGBTQI+ migrants and to allow for a certain degree of empowerment of these populations. However, some challenges have been identified, which are mainly due to the lack of resources and organizational constraints. CONCLUSIONS: The article concludes that providing psychosocial care in an integrated care setting addresses some of the barriers to accessing care faced by LGBTQI+ migrants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".