Relational Digital Agency: An Everyday Life Study of Mobile Communication in Nursing Homes
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
The pervasive association of long-term care with frailty and dependency has shaped research agendas. Everyday life studies that take into account care home residents' knowledge, values, and experiences are few and far between. This research engages care home residents in dialogue to co-produce understanding about their lived experiences with mobile technologies. Drawing on qualitative research with 39 care home residents at long-term care sites in Canada, the paper calls for reframing digital inequalities in terms of relational digital agency. The analysis describes how meaningful communication environments in long-term care involve a wide range of factors, including effective access to analogue media and wider support networks, which enable residents to put meaningful limits on their uses of mobile devices. Moreover, the findings show how having the opportunity to deny and contest mobile technologies can be an important part of feeling socially and digitally included, which brings question to existing measures of digital inclusion that focus on quantity and quality of technology use. Whereas most research on digital agency has concerned youth, this paper develops an understanding of relational digital agency to account for long-term care residents' experiences negotiating and adapting to digital change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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