Behavioural knowledge for policy design: The connection between time use Behaviours and (or) desires and support for policy alternatives
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
Abstract The study explored how understanding people's behaviours and desires can inform policy design and contribute to policy feedback theory. We focused on uses of time that are affected by diverse policies. Given the growing interest in promoting well‐being and the connection between the use of time and well‐being, we examined behaviours and desires regarding uses of time. In this exploratory study, we employed a quantitative research method. We surveyed 671 Israeli adults on their time use, desires for time use, and support for policy alternatives in three policy fields: work, education, and welfare. In five out of 11 policy alternatives, we found a connection between behavioural variables and support for policy alternatives. While exploratory, our findings contribute innovative insights into the connection between behavioural variables and support for policy alternatives related to time use. Theoretically, the article highlights the importance of incorporating behavioural ‘signalling knowledge’ as an essential input at the policy design stage and contributes to the policy feedback literature on multidisciplinary policies.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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