Public sector innovation: Sources, benefits, and leadership
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
Despite increasing research into public sector innovation, there remains a need for more theory and evidence about the sources (actors) and outcomes (benefits) of innovation. Thus, this study examines the effects of four important sources of innovation (government, organizational leaders, employee workgroup, and members of the public) on the perceived organizational benefits of innovation in the public sector. Using survey data from the Australian Public Service (n = 3,775), the findings suggest that bottom-up innovations, particularly ideas emanating from the employee workgroup, are crucial for bringing about positive effects (as measured by decreasing costs, improving processes, and increasing service quality). In contrast, ideas emanating from organizational leaders are negatively associated with organizational benefits. Nevertheless, high-quality leadership moderates the adverse effects of top-down innovations. The theoretical and practical implications of these findings, as well as future research directions for the study of public sector innovation, are discussed.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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