Austria: Joined-up government on the municipal level in Austria as coordination problem. steering of decentralised units and cross-cutting policy issues
Bibliographic record
Abstract
This volume aims to conduct a comparative analysis on both implementation and effects of joined-up reform initiatives on local government level in about eight countries, using the Pollitt and Bouckaert (2011) model of public management reform as the conceptual basis for comparison. Reforms inspired by New Public Management have raised many challenges to governments in various countries and on various levels, such as path dependencies, long time lags between implementation and results, co-ordination among different levels of government and mediocre support from public sector stakeholders. Negative effects such as fragmentation, disintegration, anomalies and paradoxes have been discussed extensively in the literature. Today we find that "Joined-up government" (JUG) modernization programs (as one strand of Post-New Public Management reforms) are increasingly implemented, and this idea can be seen to a large extent as a reaction to the effects of NPM measures (6 2004).
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".