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Record W2998164432

Understanding the role of the state in language vitality: Theoretical insights and empirical applications

2019· dissertation· en· W2998164432 on OpenAlexaboutno aff
Nicholos Poullos

Bibliographic record

VenueSummit (Simon Fraser University) · 2019
Typedissertation
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersEurostars
KeywordsVitalityState (computer science)EpistemologyData sciencePositive economicsCognitive scienceLinguisticsSociologyComputer sciencePsychologyEconomicsPhilosophyAlgorithm
DOInot available

Abstract

fetched live from OpenAlex

Canada represents an important case for research and policymaking in the area of language protection and promotion and demonstrates the need for more interdisciplinary work between sociolinguistics and political science to advance theoretical models and public policies of language vitality.Sociolinguistic research does not fully consider issues related to politics and public policy, while political science has failed to fully consider the sociolinguistic needs of language groups.This thesis contributes to the emerging field of 'normative language policy' by answering the following three research questions: 1) Do liberal states have a moral duty to support language vitality?2) What measures should the state take towards language vitality?3) Do Canada's language policies support language vitality?To answer these questions, a new Index is developed and tested with data gathered from interviews with Indigenous and Francophone stakeholders in B.C.The results suggest that these policies do not fully support language vitality.

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)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0060.013
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.345
Teacher spread0.308 · 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 designTheoretical or conceptual
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
Published2019
Admission routes1
Has abstractyes

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