Une « boîte noire » à manipuler soigneusement : L’analyse des coûts et des bénéfices sociaux de l’entreprise multinationale
Bibliographic record
Abstract
This paper assumes that the analysis of the social costs and benefits of the MNE is not only possible but also necessary. This kind of analysis is not easy because there are different rival theoretical models, because of the oligopoliste market structures that characterize multinational industries, and because the often clashing interest of home and host countries. However the author is able to identify the main costs and benefits for each group of countries. The home countries are often able to export products and factors, and to import steady flows of cheap raw materials and intermediate goods thanks to MNE. However they risk the loss of taxes, jobs and capital; besides they can suffer from MNE speculation against their own currency and balance of payments imbalances. Host countries show positive gains in terms of economic development, and eventual access to foreign markets. However they can loose taxes, suffer the extra-territorial implementation of home countries' laws and policies as well as transfer-pricing and balance-of-payments desequilibra.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".