Bibliographic record
Abstract
Cet article propose une mesure quantitative des délocalisations pour 1993, 1997 et 2003 à partir d’une base de données individuelles portant sur 15 000 établissements d’entreprises de plus de 20 salariés, permettant de dénombrer des cas avérés de délocalisations. L’analyse de ces cas confirme que les délocalisations sont un événement assez rare (environ 0,15 % des établissements concernés en moyenne annuelle). Elles résultent de trois types stratégiques (délocalisations offensives, défensives ou structurelles), et non des seuls différentiels de coût salarial. Au niveau macroéconomique, les effets ont été équilibrés grâce aux délocalisations entrantes, mais les délocalisations passées peuvent faciliter ultérieurement l’arbitrage des entreprises en faveur d’un développement plus rapide à l’étranger : les délocalisations sont une des variables d’ajustement de l’appareil industriel aux stratégies de mondialisation des 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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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".