Conducting a Mixed-Methods Study with Older Adults in Five Languages: Lessons from the Field
Bibliographic record
Abstract
One third of older adults in Canada are foreign-born, yet there is a dearth of literature on this population. When our team set out to engage in a mixed-methods study on the physical activity and mobility of foreign-born older adults (FBOAs), we found limited guidance. The objective of this Research Note is to share the lessons that we learned in implementing a mixed-methods study in five languages, with 49 visible minority FBOAs from diverse ethno-cultural groups. With an emphasis on practical implementation, here we share our reflections on early community engagement, linguistic accessibility and literacy considerations, facilitating communication with the research team, creating a support role for multilingual family members, organisational suggestions, and working with interpreters and monolingual transcribers. The older Canadian population is projected to become increasingly diverse in the coming decades, and it is our hope that this note will further facilitate research in this understudied area.
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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 | 0.246 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".