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Record W4312203194 · doi:10.15402/esj.v8i3.70403

Pathways Taken By One Canadian College to Advance Reconciliation and the Creation of a New Reconciliation Engagement Program with Indigenous Peoples

2022· article· en· W4312203194 on OpenAlexafffundvenueabout
Randy C. Battochio, Andrea Dokis, Charlene Restoule, Paige Restoule, Natasha Mayer, Mallorie Leduc, Tana Roberts

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalUniversité LavalCollège Boréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIndigenousOppressionGenocideCommunity engagementSociologyPolitical sciencePublic relationsLawEcologyPolitics

Abstract

fetched live from OpenAlex

Canada-wide efforts are being made to close the gaps that exist in the health and wellness of Indigenous Peoples besieged by a past of cultural genocide, oppression, and exploitation. The purpose of this essay is to provide members of Colleges and Institutes of Canada (CICan) access to a proposed program to engage in reconciliation, with the objective of facilitating Indigenous community engagement through social innovation, training, and applied research. The proposed program is exemplified through the relationship built between Collège Boréal and Dokis First Nation located in northern Ontario. The proposed Reconciliation Engagement Program consists of two streams that encourage CICan members to utilize, among other possible decolonizing methods, the tenets of a Critical Indigenous Methodology to value and foreground local Indigenous voices. The first stream would consist of networking activities to establish relationships, understand Chief and Council’s vision, and seek opportunities for capacity building within an Indigenous community. The second stream would be project-based so that capital costs and human resources can be accessed to complete each project. While proposing the new program is important, the present essay can also be used to exemplify how Canadian colleges and polytechnics can adopt a decolonizing approach during their engagement with Indigenous communities.

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)0.660
metaresearch head score (Gemma)0.069
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6600.069
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.6650.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.207
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 head0.079
GPT teacher head0.361
Teacher spread0.282 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2022
Admission routes4
Has abstractyes

Explore more

Same venueEngaged Scholar Journal Community-Engaged Research Teaching and LearningSame topicIndigenous Health, Education, and RightsFrench-language works237,207