Central America, China, and the Us: What Prospects for Development?
Bibliographic record
Abstract
Central America remains among the poorest subregions of Latin America, and many Central American countries are among the hemisphere’s most dependent upon primary-product exports. Unlike other commodity exporters in Latin America, however, Central American countries have not benefitted from booming Chinese demand for primary products. We use a series of measures to assess Central American countries’ trade structure, and find that they face increasing competition from Chinese products in third-country markets (like Mexico) but also little complementarity with Chinese demand (unlike Argentina or Chile). Central American countries continue to be very dependent upon the US market for exports—and, to a lesser extent, for foreign direct investment and foreign aid inflows—though dependence upon the US has slipped even as most of the countries in the subregion have entered into a preferential trade agreement with the US. The pattern of exports has shifted from agricultural to assembly plant manufactures in several countries, and Costa Rica now exports sophisticated manufactured products to the US and China alike. We explore the role that diplomatic relations may have played in Central America’s tepid China trade: all Central American countries save Costa Rica (since 2007) recognize Taiwan and not the People’s Republic of China. We end with some considerations of development strategies in the region.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.000 |
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".