MétaCan
Menu
Back to cohort
Record W2043653402 · doi:10.1080/13563467.2012.753045

Nation-State Size, Ethnic Diversity and Economic Performance in the Advanced Capitalist Countries

2013· article· en· W2043653402 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNew Political Economy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsEthnic groupDiversity (politics)State (computer science)Political scienceCapitalist stateEconomic systemPolitical economyDevelopment economicsCapitalismEconomic geographyEconomicsPolitics

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.269
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it