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Record W7120989095 · doi:10.29173/jaed565

Indigenous Economic Development Education: Aligning Curriculum with Community Aspirations

2025· article· en· W7120989095 on OpenAlexafffundabout
Tasha Brooks, Sarah Gowans

Bibliographic record

VenueJournal of Aboriginal Economic Development · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsRoyal Roads University
FundersRoyal Roads University
KeywordsIndigenousCurriculumIndigenous educationTraditional knowledgeCurriculum developmentEntrepreneurshipLocal economic development

Abstract

fetched live from OpenAlex

This research examines how postsecondary economic development curricula can align with the needs of Indigenous communities in Canada. Drawing on Indigenous research principles and mixed methods design, the study combines a literature review with semi-structured interviews (n=17) and an online survey (n=43) of Indigenous economic development practitioners and prospective students. Key curriculum priorities include leadership, governance, financial literacy, cultural competency, Indigenous knowledge systems, entrepreneurship and business skills, and legal and regulatory frameworks. Participants emphasized the central role of Indigenous economic development corporations; the importance of meaningful employment and revenue generation for community well-being; and the need to embed Elders, Indigenous instructors, and Indigenous knowledge. The findings support flexible program structures that allow students to maintain employment while participating in online learning with short in-person residency components. Overall, the study provides early guidance for designing culturally grounded economic development education that supports Indigenous self-determination, builds local capacity, and contributes to sustainable economies.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.315
Teacher spread0.302 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

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