Nation-State Size, Ethnic Diversity and Economic Performance in the Advanced Capitalist Countries
Bibliographic record
Abstract
This paper examines the proposition that the economic performance of advanced capitalist countries depends on their size and ethnic composition. As such it blends insights from two important literatures in comparative political economy. One is exemplified by the work of Peter Katzenstein, who wrote the classic treatise on the relationship between nation-state size and economic performance. Another is illustrated by the work of Ernest Gellner, whose work suggested that economic performance depends on the ethnic composition of the nation-state. The argument is tested on pooled data from 30 advanced capitalist countries for the 1985 through 2007 period. Regression analysis confirms that ethnically homogenous countries tend to have stronger rates of economic growth during this period than ethnically heterogeneous countries but that neither the size of countries nor the interaction of size and ethnic composition have significant effects. This points to the need for further exploration of these issues either with data covering a longer time frame or historical case studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".