Dividing the Grey Divide: Deconstructing Myths About Older Adults’ Online Activities, Skills, and Attitudes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although research has demonstrated a grey divide where older adults are less involved and skilled with digital media than younger adults, by treating them as a homogenous group, it has overlooked differences in their digital skills and media use. Based on 41 in-depth interviews with older adults (aged 65+ years) in East York, Toronto, we developed a typology that moves beyond seeing older adults as Non-Users to include Reluctants, Apprehensives, Basic Users, Go-Getters, and Savvy Users. We find a nonlinear association between older adults’ skill levels and online engagement, as many East York older adults are not letting their skill levels dictate their online involvement. They engage in a wide range of online activities despite having limited skills, and some are eager to learn as they go. Older adults often compared their digital media use with their peers and to more tech-adept younger generations, and these comparisons influenced their attitudes toward digital media. Their narratives of mastery included both a positive sense that they can stay connected and learn new skills and a negative sense that digital media might overwhelm them or waste their time. We draw conclusions for public policy based on our findings on how digital media intersect with the lives of East York older adults.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it