Barks and bites: dog-friendly dining experiences
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
This study investigates the leisure activity of dining out with dogs, examining the experiences of 550 Canadian dog owners through a comprehensive online survey. The research explored multifaceted aspects of dog-friendly dining, including consumer attitudes, financial implications, dog-specific menus, and the dynamics of human-canine interactions in dining settings. The findings reveal engagement with various dining formats, such as traditional restaurants, coffee shops, and fast-food establishments, highlighting a wide array of opportunities for incorporating dog-friendly practices. The study uncovered a complex interplay of interest and practical challenges in the realm of dog-friendly dining. While dog owners show a strong preference for such experiences, the industry must navigate a diverse range of consumer preferences and operational hurdles. Attitudes toward dog-friendly dining reveal a mix of positive sentiments, emphasizing inclusivity and companionship, counterbalanced by concerns over behavioural issues, hygiene, and space management. The insights from this research are valuable for stakeholders in the leisure industry, providing a basis to develop strategies that cater to dog owners while addressing operational and customer experience challenges.
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 | 0.000 | 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 | 0.000 | 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