A New Trichotomous Measure of World-system Position Using the International Trade Network
Bibliographic record
Abstract
Snyder and Kick's (1979) measure of world-system position continues to serve as the premier trichotomous network indicator of a state's location in the capitalist world economy. In this study, we identify several problems with this orthodox measure concerning its age, informal construction, and incorporation of inappropriate networks. We introduce a trichotomous network measure of world-system position that addresses these concerns, applying Borgatti and Everett's (1999) core/periphery model to a three-tiered partition using international trade data. Our trichotomous measure of the trade network identifies an expanded core, consisting of an old orthodox core joined by a set of upwardly mobile states. We estimate the effect of world-system position on economic growth and find that our trade measure significantly outperforms Snyder and Kick's orthodox measure. When controlling for human capital, the strong effects of our trade measure persist, while the weaker effects estimated by the orthodox measure largely disappear. Moreover, our models with human capital reveal that states economically converge within world-system zones, while continuing to diverge between zones.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".