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Record W2401144844 · doi:10.1177/1468796815608878

The language of conflict: The relationship between linguistic vitality and conflict intensity

2015· article· en· W2401144844 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

VenueEthnicities · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsMcGill University
Fundersnot available
KeywordsVitalityContext (archaeology)Ethnic groupPhenomenonSociologyLinguisticsSocial psychologyGroup conflictSocial conflictPsychologyPolitical scienceEpistemologyHistoryPoliticsLawAnthropology

Abstract

fetched live from OpenAlex

Intergroup conflicts represent a risk of social instability and even violence. Understanding the reasons that push group members to adopt a certain level of conflict intensity is of the utmost importance. In the hope of shedding new light into this phenomenon, this paper explores how ethnic conflict intensity may be influenced by linguistic vitality, the social health of a language. The paper presents a theoretical model in which low and high levels of linguistic vitality are presented as being linked to lower conflict intensity than moderate vitality levels. The results of multilevel modeling lend support to this hypothesis for language-based ethnic tensions in a general context and, more precisely, within countries.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.409
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.140
GPT teacher head0.383
Teacher spread0.243 · 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