Internet non-use among the Canadian older adult population: General Social Survey (GSS)
Bibliographic record
Abstract
Benefits of Internet use for older adults include the ability to access informational resources, facilitate social connections and use online communication resources. Further research on identifying the characteristics of older adult Internet non-users is warranted. The present study aims to examine the prevalence and characteristics of Internet non-use among Canada’s older adult populations. The analysis was based on the 2016 General Social Survey (GSS)– Canadians at Work and Home. Analysis was restricted to Canadians of 65 years of age or older. The outcome was Internet non-use, which was defined as having not used the Internet in the 30-day period prior to survey data collection. Demographic, socio-economic, health related, and social support and relationship factors were considered for a multivariable logistic regression analysis. Overall, the prevalence of Internet non-use among Canadian older adults was 31.9%. Characteristics significantly associated with Internet non-use included: lower educational achievement, decreased socioeconomic status, poor mental and physical health, having a partner / significant other, and being a cigarette smoker. The province of residence was significantly associated with non-internet use with residents of Quebec being at increased odds of non-internet use compared to residents of British Columbia (OR =2.09, 95% CI= 1.51-2.88). Additionally, increased age among older adults was associated with increased likelihood of not using the Internet. The findings from this study can be used as the basis for future research and to aid in the development of effective policies and programs directed towards the needs of this unique population.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".