Regions as Laboratories: the Rise of Regional Experimentalism in Europe
Bibliographic record
Abstract
With some notable exceptions the regional development debate in Europe has been dominated by exogenous models to such an extent that ‘development’ tends to be conceived as something that is introduced to, or visited upon, less favored regions (FRS) from external donors, be they states or firms. Laudable though it was in social welfare terms, this kind of regional policy did little or nothing to stimulate localized learning, innovation and indigenous development within FRS. Indeed, the latter were considered, and sometimes considered themselves, as passive receptacles for decisions taken elsewhere by others. In some of the most intractable regions — like Sicily and Campania for example — the problems of development are compounded by a corrupt and fatalistic political culture, where people feel themselves to be the powerless victims of circumstance, where local action seems pointless because, as the greatest novel of the Mezzogiorno put it, everything changes only for ‘things to stay as they are’ (Lampedusa, 1960). In these inauspicious circumstances the most important item on the developmental agenda is political reform and institutional renewal. 1 These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.022 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".