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Record W4376278569 · doi:10.1007/s10993-023-09656-5

“What is language for us?”: Community-based Anishinaabemowin language planning using TEK-nology

2023· article· en· W4376278569 on OpenAlexafffundabout
Paul J. Meighan

Bibliographic record

VenueLanguage Policy · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of CanadaInternational Research Foundation for English Language EducationMcGill University
KeywordsIndigenous languageLanguage revitalizationLanguage policyLanguage planningIndigenousMultilingualismLanguage industrySociologyPublic relationsLanguage educationPolitical sciencePedagogyComprehension approach

Abstract

fetched live from OpenAlex

Abstract Language planning and policy (LPP), as a field of research, emerged to solve the “problem” of multilingualism in newly independent nation-states. LPP’s principal emphasis was the reproduction of one-state, one-language policies. Indigenous languages were systematically erased through top-down, colonial medium-of-instruction policies, such as in Canadian residential schools. To this day, ideologies and policies still privilege dominant classes and languages at the expense of Indigenous and minoritized groups and languages. To prevent further erasure and marginalization, work is required at multiple levels. There is growing consensus that top-down, government-led LPP must occur alongside community-led, bottom-up LPP. One shared and common goal for Indigenous language reclamation and revitalization initiatives across the globe is to promote intergenerational language transmission in the home, the community, and beyond. The affordances of digital and online technologies are also being explored to foster more self-determined virtual communities of practice. Following an Indigenous research paradigm, this paper introduces theTEK-nology(Traditional Ecological Knowledge [TEK] and technology) pilot project in the Canadian context.TEK-nologyis an immersive, community-led, and technology-enabled Indigenous language acquisition approach to support Anishinaabemowin language revitalization and reclamation. TheTEK-nologypilot project is an example of bottom-up, community-based language planning (CBLP) where Indigenous community members are the language-related decision-makers. This paper demonstrates that Indigenous-led, praxis-driven CBLP, usingTEK-nology, can support Anishinaabemowin language revitalization and reclamation and more equitable, self-determined LPP. The CBLPTEK-nologyproject has implications for status and acquisition language planning; culturally responsive LPP methodologies; and federal, provincial, territorial, and family language policy.

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)0.008
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.762

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0200.011
Scholarly communication0.0070.005
Open science0.0030.010
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.145
GPT teacher head0.539
Teacher spread0.394 · 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 designQualitative
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

Citations6
Published2023
Admission routes3
Has abstractyes

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