Free time and leisure participation: international perspectives
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
1. Introduction Grant Cushman, A. J. Veal and Jiri Zuzanek 2. Australia A.J. Veal 3. Canada Jiri Zuzanek 4. Finland Mirja Liikkanen and Hannu Paakkonen 5. France Nicole Samuel 6. Germany Walter Tokarski and Harald Michels 7. Great Britain Chris Gratton and A. J. Veal 8. Hong Kong Atara Sivan, Bob Robertson and Sue Walker 9. Israel Hillel Ruskin and Atara Sivan 10. Japan Munehiko Harada 11. Netherlands Wim Knulst and Hugo Van der Poel 12. New Zealand Sue Walker, Mary Donn and Allan Laidler 13. Poland Bhodan Jung 14. Russia I.A. Butenko 15. Spain Concepcion Maiztegui-Oate 16. United States of America: Outdoor Recreation H. K. Cordell, G. T. Green, V. R. Leeworthy, R. Stephens and C. J. Betz 17. United States of America: Time-use John P. Robinson and Geoffrey Godbey 18. Conclusion Grant Cushman, A. J. Veal and Jiri Zuzanek.
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 | 0.000 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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