Leisure with dogs in the UK: the importance of shared outdoor leisure spaces highlighted by the COVID-19 pandemic
Bibliographic record
Abstract
Shared outdoor leisure spaces (SOLS) such as parks, recreation grounds, woodlands, public footpaths, and beaches provide mental, physical, and social well-being benefits for multiple users including many people with their dogs. This study explores the importance of SOLS for dog guardians, which was highlighted during the UK's first COVID-19 restrictions. Semi-structured interviews were conducted with dog guardians (n = 34). Thematic analysis was used to analyse the transcripts. Five themes were generated: one related to the impact of COVID-19 restrictions; two related to the motivators to visit, namely human intrinsic motivation and dog wellbeing benefits; and two related to the importance of SOLS as valuable community amenities and as places that provide opportunities for social interaction. Overall, results found that these spaces are very important to the daily lives of dog guardians and highly valued leisure spaces. These findings provide insights for stakeholders engaged in designing, managing, preserving, and promoting these spaces.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".