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Record W3109323240 · doi:10.7202/1071949ar

Community-Focused Language Documentation in Support of Language Education and Revitalization for St. Lawrence Island Yupik

2019· article· en· W3109323240 on OpenAlexvenueno aff
Lane Schwartz, Sylvia L. R. Schreiner, Emily Chen

Bibliographic record

VenueÉtudes/Inuit/Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignGeorge Mason UniversityGraduate College, University of Illinois at Urbana-ChampaignNational Science Foundation
KeywordsDocumentationContext (archaeology)SociologyHistoryComputer scienceArchaeology

Abstract

fetched live from OpenAlex

St. Lawrence Island Yupik, an endangered language of the Bering Strait region spoken by fewer than one thousand people in western Alaska and far eastern Russia, is currently in a state of generational transition. We survey the existing body of Yupik literature and pedagogical resources developed during the twentieth century, examine the context and use of Yupik in the current educational setting, and describe current challenges for teaching the language in the schools. We then outline our integrated approach to language documentation currently being applied to Yupik, and address how existing resources can be integrated into research and development processes in a way that both supports research efforts and results in tangible modern educational tools for the Yupik community on St. Lawrence Island, and eventually in Russia. This approach is intentionally designed to closely integrate research processes from language documentation and computational linguistics such that the results of each research endeavour positively support the other, and such that both disciplines concretely support community-based efforts to revitalize and teach the language.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.068
GPT teacher head0.487
Teacher spread0.418 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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