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Record W4417191924 · doi:10.1075/aplv.25005.gon

Rethinking (from) the Islands

2025· article· en· W4417191924 on OpenAlexaff
Wilkinson Daniel Wong Gonzales

Bibliographic record

VenueAsia-Pacific Language Variation · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSociolinguisticsVariation (astronomy)Emic and eticSalience (neuroscience)Generative grammarDisciplineColonialismMultilingualism

Abstract

fetched live from OpenAlex

Abstract This paper calls for rethinking not only studies in the Philippines but also, from them, the premises of variationist sociolinguistics. Through a grounded-theoretic thematic analysis of 77 sociolinguistic studies, it identifies seven patterns shaped by postcolonialism. Key findings show that degree of language contact does not automatically determine the social salience of differences and that most studies depart from “canonical” methodologies, prioritizing multilingualism and (post-) colonial histories/ideologies over “variable-rule” analyses. These findings motivate a dual framing: rethinking variation in the islands , which revisits Philippine sociolinguistic research as a collective, relational body of work that transcends disciplinary boundaries; and rethinking variation from the islands , which uses these insights to refine variationist theory to better account for postcolonial ecologies. While latter-wave variationism advances post-structural insights (e.g., emic perspectives, indexicality), Philippine sociolinguistics extends these by embedding them in multilingual, postcolonial contexts, advancing alternative epistemologies that position these settings as generative sites for theorizing variation itself.

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)0.002
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: none
Teacher disagreement score0.957
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.295
Teacher spread0.281 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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