Bibliographic record
Abstract
Si les géographes ont depuis longtemps reconnu l'importance des flux de capital qui sous-tendent la circulation des biens visibles, ils ont accordé peu d'attention aux mouvements internationaux de l'argent dont l'impact était difficile à mesurer. La période actuelle est marquée par la montée rapide, dans la plupart des pays, des investissements étrangers, essentiellement sous forme d'investissements directs. À la lumière de statistiques et d'ouvrages récents, l'auteur montre comment, outre l'accroissement de l'écart entre pays développés et Tiers Monde, ils modifient les réseaux de flux (biens, personnes, information, innovation) et les structures des pays d'accueil. Ils contribuent en outre à accentuer les disparités régionales, tant il est vrai que leur comportement s'identifie à travers des schémas spatiaux originaux. Certes, l'investissement américain au Canada, qui fournit les exemples les plus démonstratifs, constitue un cas limite. Néanmoins, la montée des entreprises multi-nationales engendre un nouveau système industriel caractérisé par un changement d'échelle de l'appareil de production et une modification radicale des structures et des stratégies d'entreprises.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".