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. RÉSUMÉLes espaces de loisirs partagés extérieurs (SOLS en anglais), tels que les parcs, les aires de loisirs, les forêts, les sentiers publics et les plages, offrent des avantages en matière de bien-être mental, physique et social à de multiples usagers, y compris à de nombreuses personnes accompagnées de leur chien.Cette étude porte sur l'importance des SOLS pour les gardiens de chiens, qui a été mise en évidence lors des premières restrictions du COVID-19 au Royaume-Uni.Des entretiens semistructurés ont été menés avec des gardiens de chiens (n = 34).Les transcriptions ont fait l'objet d'une analyse thématique.Cinq thèmes ont été dégagés : l'un concerne les effets des restrictions imposées par le COVID-19 ; deux concernent les motivations des visiteurs, à savoir la
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".