Finding the silver lining: aging well amongst older Brazilian women
Bibliographic record
Abstract
The aging population in Canada has been increasing steadily over the past 40 years, however, there is limited information about the meaning of aging amongst older Brazilian women. Hence, my study aimed to understand the meaning of aging well amongst older Brazilian women in the post-migration context living in the Greater Toronto Area (GTA) in Ontario, Canada. The methodology and framework used to guide my study was Heideggerian interpretive phenomenology. Eight older Brazilian women residing in the GTA were recruited through purposive and snowball sampling and participated in individual face-to-face interviews. Using van Manen’s approach to data analysis and Heidegger’s four existentials of human existence, four subthemes were developed: Embracing being part of a mosaic, Aging with grace, Chasing your dreams, and Being a bridge and not a fence. The overarching theme was: Finding the silver lining: Aging well amongst older Brazilian women. My study findings have implications for research, policy and practice to enhance the delivery of culturally responsive care to older immigrants to improve health outcomes.
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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 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".