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Record W4404017730 · doi:10.33137/tijih.v1i4.41128

Indigenous evaluation

2024· article· en· W4404017730 on OpenAlexafffund
Cassie Stefanski, Sylvia Abonyi, Richard Katz, Ruth Nicholls, Gilbert Kewistep, Donna Goodridge, Gary Groot

Bibliographic record

VenueTurtle Island Journal of Indigenous Health · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsFirst Nations University of CanadaUniversity of Saskatchewan
FundersSaskatchewan Health Research Foundation
KeywordsIndigenousGeographyBiologyEcology

Abstract

fetched live from OpenAlex

Background: Indigenous evaluation incorporates Indigenous ways of knowing and draws upon cultural paradigms (Indigenous Evaluation Toolkit, 2022). Indigenous evaluation literature is limited in both quantity and quality outcomes resulting in a lack of clarity. This scoping review was conducted to identify guiding principles, Indigenous evaluation methodologies, and explore key concepts and gaps within the literature. Methods: This scoping review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist and Arskey and O’Malley’s Scoping Review Framework. It included peer-reviewed articles and grey literature. Articles were identified through electronic database searching and reference lists using keywords. This review only included data written in English, available in full text, included keywords and identified the author and title of the publication. Articles that were not specific to Indigenous peoples or outlined Indigenous methodologies that were not related to evaluation were excluded. Results: Out of 348 articles, 94 met the inclusion criteria for this review. The literature revealed 13 guiding principles (collaboration, respect, relationships, self-determination, flexibility, trust, truth, reciprocity, power, time, sovereignty, responsibility/accountability, and relevance) and 15 Indigenous evaluation methodologies (culturally responsive, community-based, participatory, storytelling, empowerment, decolonizing, strength-based, self-reflection/location, mixed methods, talking circles, tribal critical theory, two-eyed seeing, the 4 R’s, trauma-informed approach, and ethical space). Conclusion: Key findings in this review demonstrate the need for further development of a culturally responsive Indigenous evaluation approach and for future research to outline how to put Indigenous evaluation methodologies and guiding principles into practice. Filling this gap will make a significant contribution to the field of evaluation research for Indigenous peoples, communities, and evaluators.

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)0.051
metaresearch head score (Gemma)0.135
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.725

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0510.135
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.005
Science and technology studies0.0040.003
Scholarly communication0.0090.007
Open science0.0050.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.2170.071

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 head0.155
GPT teacher head0.523
Teacher spread0.368 · 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.

Study designTheoretical or conceptual
DomainEvaluation
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

Citations4
Published2024
Admission routes2
Has abstractyes

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