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Record W6967424142 · doi:10.5281/zenodo.11078594

Metodologías de investigación incluyentes y esfuerzos comunitarios en la revitalización del idioma náhuatl

2022· article· en· W6967424142 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and XBRL
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIndigenousNahuatlSociolinguisticsFace (sociological concept)Government (linguistics)Native american

Abstract

fetched live from OpenAlex

This research paper will stimulate intercultural debate around indigenous epistemologies of the Global South. It also intends to raise awareness about the importance of indigenous languages for social development and pedagogical practices. This research is based on inclusive research methodologies with native speakers of the Nahuatl language during four fieldwork seasons between May 2017 and March 2019, inside different indigenous communities such as San Miguel Xaltipan and San Pedro Tlalcuapan in Tlaxcala, but also Santa Ana Tlacotenco in Mexico City. This research uses mixed methods (quantitative and qualitative), and one of its goals is to achieve a deeper insight into the interplay between sociolinguistics and philosophy. The data gathered are based on conversational methodologies and extended interviews with indigenous scholars, teachers, and native speakers devoted to promoting capacity building and preservation of language, traditional knowledge, and cultural heritage. Most Nahua scholars interviewed headedor collaborate with a grass-roots organization that works independently and regularly without government support or funding. Also, the academic research of Nahua scholars has been instrumental in figuring out the framework of this research. This research is based on direct translations of unpublished material from Nahuatl to English. Inclusive research methodologies help face the question: why is it important to encourage, study, and promote indigenous languages globally?

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.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0010.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.034
GPT teacher head0.240
Teacher spread0.206 · 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