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Record W7128110750

Language endangerment in Vanuatu: Bislama likely does pose a threat in the world’s most language-diverse country

2025· article· en· W7128110750 on OpenAlexaboutno aff
G. ; https://orcid.org/0000-0003-3077-7112 Lavender Forsyth

Bibliographic record

VenueMPG.PuRe (Max Planck Society) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian Indigenous Culture and History
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousFace (sociological concept)State (computer science)Traditional knowledgeQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

A quarter of a century has passed since the late Terry Crowley summed up the academic consensus that the creole language Bislama poses no immediate threat to any of Vanuatu’s Indigenous languages. Does this remain true today? Since that time, evidence both quantitative and qualitative has been accumulating that indicates Bislama is indeed gaining ground at the expense of Vanuatu’s Indigenous languages. In a targeted review of this evidence, this article brings together and assesses the insights of linguists, ethnographers, and others on the causal mechanisms that explain an ongoing shift towards Bislama. It thereby provides both a critical analysis of the current state of knowledge and a provisional causal framework for understanding current threats, predicting future threats and, potentially, intervening to prevent future threats. Language endangerment and extinction is a global issue with devastating implications for communities worldwide—one which Vanuatu, the world’s most linguistically diverse country, has thus far remained resilient in the face of. However, this review of the available evidence warns that Bislama will continue to disrupt intergenerational transmission of Indigenous languages unless a suite of inter-related mechanisms can be counteracted.

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 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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.289
Teacher spread0.280 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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