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Record W4389695869 · doi:10.1515/9780889773974-003

On the Language of the Lillooet

2014· book-chapter· en· W4389695869 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Regina Press eBooks · 2014
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsComputer scienceHistoryPhilosophy

Abstract

fetched live from OpenAlex

On the Language of the Lillooet L illooet is an Interior Salish language spoken in an area about 160 to 300 kilometres north by northeast from Vancouver.The language falls into two closely related and largely mutually intelligible dialects: a northern one, spoken in an area containing the communities of Pavilion, Fountain, Bridge River, Lillooet, and Cayoose Creek, and a southern one, spoken in Mount Currie, Samahquam, Skookumchuck and Port Douglas.The central communities of Seton Lake and Anderson Lake (D'Arcy) probably represent a mix of both dialects, but that is an issue I have not been able to explore in any detail.Long-established patterns of mutual contacts and intermarriage between the two main dialect areas have led to a further blending of the various dialects.A map of the Lillooet-speaking area is provided in Van Eijk (1997) and Van Eijk (2013), and a slightly more detailed version in Davis and Van Eijk (2014).The language went into steep decline in the twentieth century (mostly as a result of the disastrous residential school policy), but it has seen a revival in recent years, with active language classes and the ongoing output of a large number of curriculum materials in and about the language.(See www.USLCES.orgfor a catalogue of curriculum materials produced by the Upper St'át'imc Language, Culture and Education Society.)

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.905
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.023
GPT teacher head0.204
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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