Bibliographic record
Abstract
En Europe, revenir sur la vieille question des rapports métropoles-régions c’est aborder la complexité croissante des instances, des échelles et des formes de régulation de ces rapports. En effet, dans le contexte de “glocalisation” des logiques économiques, l’articulation de ces instances, échelles ou formes l’emporte sur leur succession pure et simple, par laquelle un nouvel ordre des choses remplacerait strictement l’ancien, et de nouveaux rapports métropoles-régions effaceraient les précédents. On doit donc s’efforcer de prendre en compte simultanément la vieille tendance à l’intégration des espaces (métapolisation) dans des “villes-régions” (1.), la résistance des nécessaires régulations nationales entre régions métropolisées et régions non métropolisées (2.), et la lente formation de nouveaux dispositifs transnationaux d’organisation spatiale d’intérêt européen (3.). Ce qui conduit à s’interroger sur l’émergence de fait d’un “État glocal” aux dimensions des enjeux de régulation de rapports qui s’établissent aux échelles à la fois régionale, nationale et supranationale (4.).
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 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 | 0.003 | 0.013 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.003 |
| 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".