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Record W2125024855 · doi:10.1177/0020715204049591

Empire, Race, and Ethnicity

2004· article· en· W2125024855 on OpenAlexvenueno aff
John Rex

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsHegemonyModernization theoryEthnic groupCommunismContext (archaeology)RefugeePolitical sciencePolitical economySociologyPower (physics)EmpireWorld War IIGender studiesPoliticsLawHistory

Abstract

fetched live from OpenAlex

The year 2005 will mark sixty years since the end of the Second World War. During that time, social scientists have tried to conceptualize the world in terms of race and ethnic relations. Old imperial orders collapsed and a process of liberation from White domination in South Africa had already begun within the context of the Cold War. At the same time, a process of modernization began in the imperial metropolises, leading to the emergence of a kind of Welfare State designed to overcome class conflict, but having to cope with the integration of sub-national and migrant minorities. In 1989, the bipolar power situation, internationally, ended with the collapse of Communism. There occurred a new transfer of populations; refugees replaced economic migrants as the principle group that had either to be integrated or become the major focus of national conflicts. Internationally, American world hegemony came into being. America and its subordinate allies saw themselves as faced with a wide range of resistance taking the form of terrorism, but also with new rogue states as their enemies. This paper reviews the ways in which race and ethnic relations have been conceptualized at various stages in this process.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.058
GPT teacher head0.418
Teacher spread0.360 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Comparative SociologySame topicMigration, Refugees, and IntegrationFrench-language works237,207