Online privacy concerns and privacy protection strategies among older adults in East York, Canada
Bibliographic record
Abstract
Abstract As news headlines report on high‐profile online privacy breaches and the potential negative consequences for users, users are becoming concerned about their privacy. While much research has focused on the concerns of younger generations, few studies have investigated older adults, specifically those aged 65+ years. This study analyzes in‐depth interviews with 40 older adults living in East York, Toronto, Canada, to investigate their online privacy concerns and the strategies they use to mitigate these concerns. We find that East York older adults are mostly concerned about security privacy concerns followed by institutional privacy concerns and only minimally concerned about social privacy. The greatest concerns included information misuse by unknown others and unauthorized access to their personal information. We found that, for some older adults, their high privacy concerns precluded them from taking full advantage of the potential benefits of digital media. East York older adults varied considerably in their use of privacy protection strategies; some older adults used no strategies, while others were eager to protect their privacy using all strategies at their disposal.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".