Aléas des stratégies de diversification technologique des nouveaux pays industriels
Bibliographic record
Abstract
En règle générale, la théorie accueille favorablement les tentatives de diversifications technologiques auxquelles se sont livrées certains nouveaux pays industriels, à partir des années 70. L’expérience a cependant mis en lumière, dans le cas des ambitieux programmes électronucléaires du Brésil et de la Corée du Sud, les coûts et les difficultés particulières, voire quelquefois insurmontables, que pose la stratégie de diversification vis-à-vis des pays fournisseurs de technologie. Comme on le sait, celle-ci implique nécessairement une multiplication et une complexification des technologies elles-mêmes. Freeman propose, pour évaluer la prestation des NPI dans le processus d’acquisition, trois séries de facteurs explicatifs qui tiennent bien davantage à leur propre structure d’accueil — administrative, scientifique et industrielle — qu’à l’évolution de la conjoncture, donc des facteurs internationaux. Cet article se propose de révéler les zones de succès, mais aussi les lacunes du dispositif local d’encadrement du transfert technologique, qu’il s’agisse des agences gouvernementales ou des institutions responsables de la formation et de la maîtrise technologique.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".