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Record W2093467881 · doi:10.5539/ass.v11n7p252

Conflict Potential of Interethnic Relations and Migration Processes in the Russian Regions: Ethnoinstitutional Methodology of Analyses

2015· article· en· W2093467881 on OpenAlexvenueno aff
Elena Yurievna Bazhenova, Антон Владимирович Сериков, Ирина Борисовна Серикова, Darya Nikolaevna Stukalova

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupPopulationCollective identityIdentity (music)Host (biology)SociologyPolitical economyPolitical scienceEconomic geographyEconomic systemDevelopment economicsSocial psychologyGeographyEconomicsBiologyPsychologyLawEcologyPoliticsAnthropologyDemography

Abstract

fetched live from OpenAlex

The article defines ethnoinstitutional factors in migration and interethnic relations. Ethnic institutions(ethnoinstituions) are regarded as stable complexes of individual and collective behavioral norms andmotivations, mediated by ethnic culture and identity. The article shows that the conflict potential of migration isprimarily associated with incompatibility of host and arriving population ethnoinstitutions. It is necessary todevelop transmitting institutions to reduce the conflict potential of interethnic relations. Such institutions shouldbe able to “translate” ethnoinstitutional requirements of the host community in the form which will motivatemigrants to accept the local rules and behavior patterns.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.283
GPT teacher head0.450
Teacher spread0.166 · 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 designQualitative
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

Citations1
Published2015
Admission routes1
Has abstractyes

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