The Canadian Longitudinal Study on Aging: A Vehicle for Research on Aging in Older Veterans
Bibliographic record
Abstract
INTRODUCTION: Research on the health of older Veterans in Canada is an emerging area. Few population-based studies in Canada have included older Veterans as a specific group of interest. This paper describes a cohort of self-identified Veterans within the Canadian Longitudinal Study on Aging (CLSA). MATERIALS AND METHODS: Using data from the CLSA baseline assessment (2011-2015), we describe sociodemographic and health characteristics along with military-related variables in a cohort of Veterans in Canada. We also estimate the number of Canadian and non-Canadian Veterans living in Canada at the time of the CLSA baseline data collection. RESULTS: We estimate that at the CLSA baseline, there were 718,893 (95% confidence interval [CI], 680,033-757,110) Canadian Veterans and 185,548 (95% CI, 165,713-205,100) non-Canadian Veterans aged 45-85 years living in Canada. Veterans were older and predominantly male compared to non-Veterans in the CLSA. Following age and sex adjustment, the distribution of sociodemographic and health characteristics was similar across all groups. The majority (> 85%) of participants in each comparison group reported self-rated general and mental health as excellent, very good, or good. Following age and sex adjustment, most characteristics across groups remained similar. One exception was mental health, where a greater proportion of Veterans screened positive for depression and anxiety relative to non-Veterans. CONCLUSIONS: Using CLSA baseline data, we estimate the number of older Veterans in Canada and present descriptive data that highlight interesting differences and similarities between Veterans and non-Veterans living in Canada. Canadian and non-Canadian Veterans in the CLSA are presented separately, with the latter group having not been previously studied in Canada. This paper presents a snapshot of a cohort of self-identified Veterans within the CLSA at study baseline and highlights the potential of the CLSA as a vehicle for studying the aging Veteran population in Canada for years to come.
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How this classification was reachedexpand
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".