Visual impairment, employment status, and reduction in income: the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVE: To examine the employment status of those with and without visual impairment and eye disease and to examine the association between visual impairment and eye disease and a reduction in income over a 3-year period. DESIGN: Population-based prospective cohort study. PARTICIPANTS: A total of 12,174 nonretired participants aged 45-64 years old in the Canadian Longitudinal Study on Aging. METHODS: Visual impairment was defined if binocular presenting or pinhole-corrected monocular visual acuity in the better eye was worse than 20/40 at baseline. Self-reported diagnoses of age-related macular degeneration (AMD) and glaucoma were collected. Employment status (employed, not employed due to sickness or disability, or unemployed) was based on questions on labour force participation. Income reduction was defined as household income <$50,000 per year at follow-up when household income was ≥$50,000 at baseline. Multinomial and logistic regressions were used to adjust for demographic and health variables. RESULTS: Visual impairment using binocular presenting visual acuity (odds ratio [OR] = 2.09; 95% CI, 1.21-3.62) and pinhole-corrected visual acuity (OR = 2.99; 95% CI, 1.54-5.83) were associated with a higher odds of not being employed due to sickness or disability after adjustment. AMD (OR = 1.82; 95% CI, 1.11-3.01) and glaucoma (OR = 2.05; 95% CI, 1.28-3.28) at baseline were both associated with reductions in income over a 3-year period after adjustment. CONCLUSION: Individuals with visual impairment experienced lower employment, and those with AMD or glaucoma were more likely to have their incomes decline over 3 years. Policies to improve workplace participation by those with vision loss are needed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".