Environmental Determinants of Public Sector Innovation: A study of innovation awards in Canada
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
In this article, we conduct an empirical study of administrative innovation in the Canadian public sector by examining applications to the Innovative Management Award of the Institute of Public Administration of Canada (IPAC). After a review of the literature on innovation in the public sector and of the history of this award, we come to the conclusion that the relationship between innovation and environment has been studied only sparingly, which explains the focus of our research and our hypotheses. Through an analysis of award applications over 21 years, and of award finalists and winners, we demonstrate that such environmental variables as strength of the economy, size of the civil service, deficits, unemployment rate, investment in R&D, and type of government have important consequences for administrative innovation in the public sector. We also suggest some implications of our findings for future research on this subject.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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