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Record W4388666181 · doi:10.54056/pscj2651

The Emerging Indigenous Language Economy: Labour Market Demand for Indigenous Language Skills in the Upper Great Lakes

2019· article· en· W4388666181 on OpenAlex
Sean Meades, Deb Pine, Gayle Broad

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Aboriginal Economic Development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousIndigenous languageHuman capitalSociologyPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

Language revitalization is necessarily intertwined with economic spheres, as Grenoble and Whaley have expressed that the economic wellbeing of a community influences its ability to engage in such efforts (2006, p. 44). Conversely, health researchers assert that cultural continuity, in which language is inextricably linked, is a prerequisite to self-sufficiency and community sustainability (Oster, Grier, Lightning, Mayan, & Troth, 2014). Nonetheless, the place of Indigenous language(s) within labour market research has often focused on the need for greater access to dominant-language education (MacIsaac & Patrinos, 1995) or the impact on wage differentials (Chiswick, Patrinos, & Hurst, 2000) while research on Indigenous language revitalization in Canada has been largely silent on the relationship to economic spheres, and community economic development literature has engaged with notions of culture more broadly. Drawing on interviews and focus groups from a selection of Anishinaabe communities in Northern Ontario, Canada, this research identifies existing needs for Anishinaabe language speakers within the regional labour market, showcasing the oft-overlooked economic demand for Indigenous language skills. Support for this project was provided by the Ontario Human Capital Research and Innovation Fund from the Ministry of Training, Colleges and Universities.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.003
GPT teacher head0.245
Teacher spread0.241 · 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