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
The relationship between slack resources and innovation is complex, with the literature linking slack to both breakthrough innovations and resource misallocation. We reconcile these conflicting views by focusing on a novel mechanism: the role slack time plays in the endogenous allocation of time and effort to innovative projects. We develop a theoretical model that distinguishes between periods of high- (work weeks) versus low- (break weeks) opportunity costs of time. Low-opportunity cost time during break weeks may induce (1) lower quality ideas to be developed (a selection effect); (2) more effort to be applied for any given idea quality (an effort effect); and (3) an increase in the use of teams because scheduling is less constrained (a coordination effect). As a result, the effect of an increase in slack time on innovative outcomes is ambiguous, because the selection effect may induce more low-quality ideas, whereas the effort and coordination effect may lead to more high-quality, complex ideas. We test this framework using data on college breaks and on 165,410 Kickstarter projects across the United States. Consistent with our predictions, during university breaks, more projects are posted in the focal regions, and the increase is largest for projects of either very high or very low quality. Furthermore, projects posted during breaks are more complex, and involve larger teams with diverse skills. We discuss the implications for the design of policies on slack time. The online appendices are available at https://doi.org/10.1287/orsc.2018.1215 .
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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