Vieillissement et perte de mémoire : avis de migrants haïtiens résidant au Québec
Bibliographic record
Abstract
INTRODUCTION: ‘Dementia’ is usually presented as a syndrome characterized by the decline of one or more cognitive abilities such as memory loss. However, memory loss does not necessarily mean dementia. The most common type of dementia is Alzheimer’s disease. Its incidence increases with age. In medical anthropology, diseases represent socio-cultural constructs that are not recognized and interpreted in the same way by everyone. Moreover, the migratory context is a source of difficulties in the field of dementia. In this article, we discuss the links between old age, dementia and seeking help in this context. METHOD: This is an exploratory qualitative study. Ten semi-structured interviews were conducted with women and men born in Haiti who then immigrated to Quebec. These interviews allowed us to discuss seniors’ status issues, the meaning of memory loss and seeking help. RESULTS: Interview data reveal a plurality of representations about memory loss and Alzheimer’s disease. They highlight a diversity of beliefs, attitudes and values that reflect cultural and social changes within the same community. Taking into account the context makes it possible to consider the transformation or continuity of representations and behaviors vis-à-vis loss of memory. CONCLUSION: Dementia does not seem to be a phenomenon that is easily approached in the Haitian community in Quebec. Our study reveals a lack of information in this regard.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".