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Record W3089104608

Prolonged multilingualism among the Sebuyau: An ethnography of communication

2020· dissertation· en· W3089104608 on OpenAlexfundno aff
Stanley Anonby

Bibliographic record

VenueSummit (Simon Fraser University) · 2020
Typedissertation
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaSimon Fraser UniversityStyrelsen för Internationellt Utvecklingssamarbete
KeywordsMultilingualismEthnographyLinguisticsSociologyAnthropologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

This thesis describes the Sebuyau language and seeks to explain how this small group as maintained their culture and way of speaking in the shadow of very large languages like Malay, English and Chinese. I use the ethnographic method to study this ethnic group. Specifically, I based this ethnography of communication on two texts told by twenty-four people, who all belong to the community of practice of Keluarga Church. The study is divided into two broad areas. Part of the thesis is more synchronic linguistics, and describes the lexicon, phonology and morphology of Sebuyau. The conclusion is that Sebuyau is a variety of Iban. The lexicon exhibits considerable borrowing from languages that are no longer spoken in the area – such as Sanskrit. But most of the non-Sebuyau words are English or Malay. There are some lexicographic signs of the beginning of language shift to Malay, but the phonology shows signs that the language is being reincorporated into Iban. The other theme of the thesis is an examination of the reasons why Sebuyau has not been swallowed up by Malay or some other language. It is a more general description of the history and linguistic ecology of the area in Malaysia that is their homeland. In particular, the study shows how the linguistic ecology has helped the Sebuyau maintain their identity and way of speaking.

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)0.000
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 score0.499
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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