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Record W4205343540 · doi:10.17759/chp.2021170401

A Taxonomy of Intergroup Ideologies

2021· article· en· W4205343540 on OpenAlexaff
Dmitry Grigoryev, John W. Berry

Bibliographic record

VenueCultural-Historical Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsQueen's University
FundersRussian Science Foundation
KeywordsIdeologyTaxonomy (biology)HierarchySociologyDiversity (politics)Cultural diversitySocial psychologyEpistemologyGender studiesPolitical sciencePsychologyPoliticsEcologyAnthropologyLawPhilosophy

Abstract

fetched live from OpenAlex

This paper provides an analysis and a general taxonomy of intergroup ideologies, and presents a list of their indicators. This taxonomy is related to the eight ideologies that were originally outlined in the early works. These ideologies were created on the basis of three dimensions of intercultural relations: cultural maintenance; social participation; and relative power. The taxonomy of intergroup ideologies proposed here follows these three dimensions, which are related to two issues: (i) attitudes towards cultural diversity; and (ii) forms of inclusion of ethnocultural groups in the larger society (including the issue about the hierarchy among groups). It is possible to assess how these issues are solved using four indicators: (1) celebrating differences, (2) status of groups, (3) opportunity for social interaction, and (4) way to ensure the unity of society. Orientations to these indicators make it possible to understand what kind of intergroup ideologies covering intercultural attitudes and intergroup relations exist in countries and describe them.

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0160.009
Science and technology studies0.0050.006
Scholarly communication0.0070.013
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.275
GPT teacher head0.428
Teacher spread0.153 · 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 designTheoretical or conceptual
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

Citations19
Published2021
Admission routes1
Has abstractyes

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