Policies for Territorial Rebalancing in the Era of the National Recovery and Resilience Plan (PNRR). New Indicators for the Classification of Inner Areas in Italy
Bibliographic record
Abstract
In February 2022, the Department for Planning and Coordination of Economic Policy (CIPESS) published the update of the Italian Inner Areas Map (2020), integrating the classification of 2014. In this update, the analysis tools were revised, returning more precise results, but both indicators and methodology did not change. \nThe definition of Inner Areas by the Agency for Territorial Cohesion identifies those "areas that are significantly distant from the centres offering essential services (education, health and mobility), rich in important environmental and cultural resources; about a quarter of the Italian population lives here, in a portion of territory that exceeds 60% of the total territory and is organised into more than four thousand municipalities". The distance between each municipality to the service provider centre is still calculated on the average of road travel time during weekday peak hours (pre-Covid19). This type of classification, further than minimizing the role of public transport infrastructures, distorts the reading of the territory ignoring other economic-social, cultural, of telematic accessibility and of environmental protection factors. \nThe National Recovery and Resilience Plan (PNRR) now offers the opportunity to revise the policies for territorial re-balancing in Italy. \nThis paper intends to present the key points of a research that analyses the current methods and criteria for classifying Inner Areas. With the aim of developing a homogeneous territorial mapping tool, better suited to the purposes of territorial cohesion, the objective of the research will be to define a new method of classifying Inner Areas and fragile territories, based on several essential integrated indicators and on experimenting consolidated methods in the framework of: \n•\tsocio-economic analyses, such as the Local Employment Systems (ISTAT); \n•\tidentification of urban and rural areas, beyond the thresholds of administrative boundaries, such as Local Action Groups (GALs); \n•\tfiscal analysis, such as the reading of per-capita taxable income gap.
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.
How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".