Les enjeux de santé mentale chez les aînés gais et lesbiennes
Bibliographic record
Abstract
Most gay and lesbian elders have experienced discrimination and stigmatization related to their sexual orientation in their life trajectory. These negative experiences may have had an impact on their life course and on their mental health. Even if the majority of gay and lesbian older adults actually have and maintain good mental health, studies show that non-heterosexual people are at a greater risk of developing certain difficulties, such as anxiety, depression, suicidal thoughts and excessive consumption of alcohol and other substances. This article presents the factors that may weaken the mental health of older gay and lesbian people, such as victimization and the exposure to various forms of prejudice in their life course, the continuous management of the disclosure or dissimulation of their sexual orientation, the degree of internalized homophobia, as well as loneliness; and also presents the potential protective factors, such as building resilience, social networks and social support. This article concludes by illustrating the implications concerning the specific needs of the gay and lesbian elders. Some recommendations are also formulated with regards to recognizing the issues affecting gay and lesbian older adults as well as improving the services that are offered to them.
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.
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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".