Culturally Responsive Supports for Metis Elders and Metis Family Caregivers
Bibliographic record
Abstract
Malgré une attention académique considérable au rôle de la famille des soignants avec la population générale, peu de recherches ont été menées avec les familles autochtones. Cette étude qualitative vise à combler cette lacune en se concentrant sur l'expérience des soignants Metis, fournir des soins aux adultes Metis plus âges. Des groupes de discussions et des entrevues ont été menés avec des aidants familiaux Metis (n - 79), aînés Metis (n - 11), et soignants officiels (n - 8). Bien qu'il existe de parallèles considérables dans les expériences des soins identifiés dans cette étude sur les Metis avec celles déjà documentées dans la littérature, il existe néanmoins des différences importantes pour la prestation des soins culturellement adaptés aux aînés Metis. Despite considerable academic attention to the role of family caregivers within the general population, little research has been conducted with Indigenous families. This qualitative study aims to fill that gap by focusing on the experiences of Metis caregivers providing care for older Metis adults. Focus groups and interviews were conducted with Metis family caregivers (n = 79), Metis Elders (n = 11) and formal caregivers (n = 8). Although there are considerable parallels in the caregiving experiences identified in this Metis study with those already documented in the literature, there are nonetheless important differences for providing culturally responsive care to Metis seniors.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 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".