Composite Index for Quality of Life in Italian Cities: An Application to URBES Indicators
Bibliographic record
Abstract
Il Benessere Equo e Sostenibile nelle citt¨¤ (URBES) Report, drawn up by the Italian Institute of Statistics (ISTAT) offers a set of relevant indicators to assess the quality of life (QoL) in fourteen big Italian cities. These indicators belong to the twelve dimensions of well-being identified by Benessere Equo e Sostenibile (BES), the dashboard of indicators provided by ISTAT and the National Council of Economy and Labour (CNEL) in 2013 to evaluate the differences in well-being among the Italian regions. Our paper uses this set of data to highlight the Italian urban situation, through the construction of a composite indicator. The selected methodologies to do that are additive model, factorial analysis and Borda method. We obtain a ranking that shows what context can allow positive levels of QoL. This study drops in a critical phase: Italian territorial administration is going to be modified and ¡°Metropolitan Cities¡± will be assumed an increasingly important role.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".