LGBTQIA+ Elderly: How male gay men are affected by etarism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The elderly population (60 years or older) is the fastest growing in Brazil. By 2060 these individuals will represent a quarter of the Brazilian population, at least 25.5%, according to IBGE (Brazilian Institute of Geography and Statistics) data from 2018. For this reason, both political, social, psychological, and health issues, as well as Geriatrics and Gerontology intensify their assessment and methodology, to adapt to all these problems that grow exponentially over time (Camarano and Kanso, 2010). The present work seeks to develop research related to how the different prejudices (homophobia and etatism) directed to the people of this population affected/affect their future, their present, and their past with a focus on the LGBTQIA+ population, focusing on the cut of gay men of this community, to understand how these people lived and how they were of Homophobia in times when they needed to hide their sexuality, how it affected or affects the way they perceived themselves back then and how they perceive themselves today, being elderly people and being within the LGBTQIA+ community, through semi-structured online entertainment. The adversities in the living conditions that this population faces can cause serious psychological problems, adding this to the lack of knowledge and research in this area, explains that aging within the the LGBTQIA+ community is an aspect of this population that needs to be discussed and studied, thus contributing to a better quality of life and aging of these people, without stigmas or prejudices.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it