‘We have different routes for different reasons’: Exploring the purpose of walks for carers of people with dementia
Bibliographic record
Abstract
This paper explores the purpose of walks for co-residing carers of people with dementia, using a social citizenship lens. The findings are based on the first phase of a study examining the everyday experiences of place, space, and neighbourhood of dementia carers. Using three forms of data collection - social network mapping, walking interviews, and participant-driven photography - the study brings forth information about why carers go on walks either alone or with the person with dementia. Carers explained that walks facilitate their connections with themselves, the person with dementia, their social environment, and their natural and built environment. In sum, walks provide a way of practicing and sustaining social citizenship. Carers' discourse about walks highlights their personal, everyday practices and strategies, as well as the larger tensions and contradictions of dementia care. The findings reinforce the need to bring into dialogue, from a carer perspective, a social citizenship model of dementia with the growing interest in dementia-friendly communities.
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.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".