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Record W3171439599 · doi:10.1515/opli-2021-0010

Nahuatl, selected vitality indicators and scales of vitality in an Indigenous language community in Mexico

2021· article· en· W3171439599 on OpenAlexaff
Grace A. Gomashie, Roland Terborg

Bibliographic record

VenueOpen Linguistics · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Cultures and Socio-Education
Canadian institutionsWestern University
Fundersnot available
KeywordsNahuatlVitalityIndigenousPopulationIndigenous languageLinguisticsSpeech communityPsychologyGeographySociologyDemography

Abstract

fetched live from OpenAlex

Abstract Scales or measurements of vitality propose various factors to assess the degree of endangerment of a language. Using these measurements offers important insights into the maintenance of a language and identifies the areas in need of support. The current study employed seven scales to assess the vitality of Nahuatl in the language community of Puebla, Mexico. Data on the selected vitality indicators, absolute speaker population, and intergenerational language transmission were collected through questionnaires on linguistic knowledge and home language use. Results showed that five out of the seven scales characterized Nahuatl as not at an immediate risk of endangerment as it had speakers in all age groups and was spoken at home by them. However, there was need for more emphasis on transmitting Nahuatl to the younger generations who made up the majority of the non-Nahuatl speaker population and were more likely to use Spanish than Nahuatl. The approach taken by this study will be of value when assessing other communities facing language endangerment and seeking language maintenance and revitalization.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.024
GPT teacher head0.388
Teacher spread0.364 · 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 designObservational
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

Citations9
Published2021
Admission routes1
Has abstractyes

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