The emergence of post-NPM initiatives: Integrated Impact Assessment as a hybrid decision-making tool
Bibliographic record
Abstract
Despite the criticism levelled at it, New Public Management (NPM) seems to be enduring. Post-NPM initiatives remain relatively theoretical and are slow to take root at the heart of the governmental apparatus. Integrated Impact Assessment (IIA), a tool for decision-making at national level, seems to be providing new answers. IIA has developed from NPM regulatory relief initiatives, but its objectives and effects are more in line with post-NPM principles. This article aims to explore the concept of IIA, its development and the implications of its institutionalization. A comparative analysis of IIA practice is carried out for four approaches: three at the national level (France, United Kingdom and Switzerland) and one at the supranational level (European Commission). IIA appears as a hybrid NPM and post-NPM tool, the use of which allows the implementation of certain post-NPM principles. The article concludes on future avenues for research. Points for practitioners Administrations often have to deal with issues related to evidence-based decision-making, transparency and the proliferation of statutory sectoral impact assessments. In a context of limited resources, Integrated Impact Assessment (IIA) can be an attractive solution. However, a careful analysis of its development makes it possible to better understand what its institutionalization actually implies. The practice of IIA makes it possible to systematize consultation with stakeholders, but varies according to the methods used and the administrative structures in place. IIA could serve as a decision-making tool that adds a public interest component and better reflect public values in a decision-making situation.
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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 | 0.158 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.030 | 0.025 |
| Open science | 0.005 | 0.021 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".