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Record W4313287814 · doi:10.22543/1948-0733.1428

Anishinaabe Values and Servant Leadership: A Two-Eyed Seeing Approach

2022· article· en· W4313287814 on OpenAlexaff
Tori McMillan

Bibliographic record

VenueJournal of Values-Based Leadership · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican cultural and philosophical studies
Canadian institutionsMount Royal University
Fundersnot available
KeywordsIndigenizationServant leadershipServantIndigenousSociologyPerspective (graphical)DecolonizationPolitical scienceEnvironmental ethicsPublic relationsLeadership styleLawPhilosophyAnthropologyPoliticsEngineering

Abstract

fetched live from OpenAlex

This meta-synthesis explores the connections between the Mishomis Teachings (also known as the Seven Grandfather Teachings within the Anishinaabe culture) and the principles of Servant Leadership. Through a systematic literature review of methodology and the theoretical frameworks of Two-Eyed Seeing and Ethical Space, The Mishomis Teachings and their connections to Servant Leadership are researched to answer: How is a Two-Eyed Seeing approach to Servant Leadership informed by Anishinaabe Values? The literature reveals significant connections between the Mishomis Teachings and Servant Leadership that provide an Indigenized perspective on values-based leadership practices. The implications of this study highlight a growing need within academia for Indigenous Knowledge to support and enhance Decolonization, Indigenization and Reconciliation efforts.

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)0.028
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.040
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0090.006
Science and technology studies0.0030.007
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.228
GPT teacher head0.330
Teacher spread0.102 · 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 designTheoretical or conceptual
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

Citations4
Published2022
Admission routes1
Has abstractyes

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