Many older people felt that electronic care surveillance increased their safety and enabled them to live alone in their own homesCommentary
Bibliographic record
Abstract
A Essen Dr A Essen, School of Business, Stockholm University, Stockholm, Sweden; aes@fek.su.se How do older people who live with telemonitoring devices feel about their privacy? In-depth interviews. Participants’ homes in Sweden. A purposeful sample of 17 participants 68–96 years of age (53% women) who had been monitored for at least 6–7 months by a telemonitoring device, lived alone, and were exposed to potential health risks in their own homes. In-depth, face-to-face interviews were conducted, each lasting 90–120 minutes. Questions were asked about participants’ experiences with their telemonitoring devices followed by a discussion of privacy and privacy threats. Interviews were recorded, transcribed, translated, and analysed for themes using an iterative process; notes were taken on non-verbal cues (ie, appearance, anxiety). 2 contrasting perspectives were found. (1) Care surveillance as enabling (n = 16). Most participants with telemonitoring devices felt privileged and cared …
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".