GOVERNANCE MODEL IN THE ITALIAN PUBLIC ENTITIES AFTER MORE THAN A QUARTER OF A CENTURY SINCE THE REFORM
Bibliographic record
Abstract
This work begins by analysing the different types of organizational models, identifiable in the Public sector when considering, simultaneously, two different variables: \n1.\tthe distribution of power between politicians and managers; \n2.\tthe nature of the managers employment contracts. \nAfter this first study, it is possible to identify the model of governance “traditionally” used in Italy. The “traditional” period ended when during the 90s, a new reform was introduced which invaded the organizational aspect of public Administrations. With this reform, Italy presented a “modern” model of governance. \nNow, more than 25 years since the principle of distinction was introduced, it is time that we try to answer some questions: \n-\tIs, the “modern” model – introduced by reform - effectively applied? \n-\tIs it true that as a result of the introduction of the principle of distinction, the functions assigned to the politicians and executives are identified and managed in the best possible way? \n-\tHas this led to the management of the institution more efficient? \nWith respect to the regulatory framework in force, can distinguished politicians more or less "enlightened" from those more or less "retrograde", as well as the managers substantially "bureaucrats" by those who may have more or less "leaders" attitudes, thus identifying 4 types of public Administrations. \nThis first study is a prerequisite for the development of an organizational-accounting instrument necessary for a future empirical examination in Italian public entities.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".