Bibliographic record
Abstract
Small nations fear that FTAs with larger, richer nations will erode their industrial bases. These concerns are recognized in FTA and multilateral talks: small nations may explicitly or implicitly maintain higher trade barriers. Using a model where symmetric liberalization de‐industrializes small, poor nations, we characterize the path of protection‐asymmetries that allow liberalization without delocation. In welfare terms, the large nation prefers this no‐delocation liberalization scheme only when barriers are sufficiently high; the small nation's ranking is reversed. An anti‐delocation scheme involving international income transfers is also evaluated and found infeasible. Accords de libre‐échange quand il y a délocalisation. Les petits pays craignent que les accords de libre‐échange avec des pays plus grands et plus riches n'entament leur base industrielle. Ces malaises sont reconnus dans les négociations bilatérales et multilatérales: on permet aux petits pays de maintenir explicitement ou implicitement des barrières commerciales plus élevées. A l'aide d'un modéle où la libéralisation des échanges engendre une désindustrialisation des petits pays pauvres, les auteurs identifient les niveaux d'asymétrie dans le niveau de protection qui permettent d'engendrer une désindustrialisation sans délocalisation. En termes de niveau de bien‐être, le grand pays préfère cet arrangement sans délocalisation seulement quand les barrières commerciales sont suffisamment élevées; la préférence des petits pays est à l'inverse. On évalue un arrangement sans délocalisation impliquant des transferts internationaux de revenus, et on montre qu'il est impraticable.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.053 | 0.006 |
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".