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Record W3167517705 · doi:10.1177/19427786211022899

Language is land, land is language: The importance of Indigenous languages

2021· article· en· W3167517705 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

VenueHuman Geography · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMcGill UniversityYork University
Fundersnot available
KeywordsIndigenousIndigenous languageTraditional knowledgeLanguage revitalizationLinguisticsGeographySociologyEcologyBiology

Abstract

fetched live from OpenAlex

This collaborative opinion piece, written from the authors’ personal perspectives (Anishinaabe and Gàidheal) on Anishinaabemowin (Ojibwe language) and Gàidhlig (Scottish Gaelic language), discusses the importance of maintaining and revitalizing Indigenous languages, particularly in these times of climate and humanitarian crises. The authors will give their personal responses, rooted in lived experiences, on five areas they have identified as a starting point for their discussion: (1) why Indigenous languages are important; (2) the effects of colonization on Indigenous languages; (3) the connections/responsibilities to the land, such as Traditional Ecological Knowledge (TEK), embedded in Indigenous languages; (4) the importance of land-based learning and education, full language immersion, and the challenges associated with implementing these strategies for Indigenous language maintenance and revitalization; and (5) where we can go from here.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.362
Teacher spread0.343 · 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