Bibliographic record
Abstract
On s’interroge, dans cet article, sur la pertinence de la thèse de l’écart croissant entre les niveaux de vie des pays pauvres et riches. Celle-ci n’est pas neuve mais fait actuellement un retour en force dans le cadre des débats suscités par la mondialisation et l’anti-mondialisme. S’appuyant sur des séries statistiques sérieuses et récentes, l’auteur établit tout d’abord que la notion d’écart « global », fort difficile à cerner, n’a pas grand sens et qu’en outre le désir ou l’espoir d’une « convergence » à court ou moyen terme des deux ensembles de pays relève plutôt du rêve. Puis, dépassant cette vision probablement trop globalisante de la question examinée, il montre que les diverses évolutions nationales, (notamment les croissances démographiques et économiques) de bien des pays moins développés, conduisent à douter de la validité « absolue » de la thèse de l’écart croissant et à nuancer fortement les conclusions les plus fréquemment avancées, excessivement pessimistes selon lui.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".