Loose Cannons and Rule Breakers, or Enterprising Leaders? Some Evidence About Innovative Public Managers
Bibliographic record
Abstract
One element of the debate over New Public Management concerns public‐sector entrepreneurship. Critics see entrepreneurs as people prone to rule breaking, self‐promotion, and unwarranted risk taking, while proponents view them as exercising leadership and taking astute initiatives. This article examines two samples of the best applications to the Ford Foundation—Kennedy School of Government innovation awards, one between 1990 and 1994 and the other between 1995 and 1998, to see whether they are more consistent with the critics' or proponents' views. The second sample closely replicates the first, and the evidence from both strongly supports the proponents' views. Innovators are creatively solving public‐sector problems and are usually proactive in that they deal with problems before they escalate to crises. They use appropriate organizational channels to build support for their ideas. They take their opponents seriously and attempt to win support for their ideas through persuasion or accommodation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".