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Record W6889659411 · doi:10.26181/22708264

Transformational Mentoring Experiences for First Nations Young People: A Scoping Review

2023· article· en· W6889659411 on OpenAlexaboutno aff

Bibliographic record

VenueLa Trobe University · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsAotearoaTransformational leadershipNarrativeEthnographyInclusion (mineral)Transformative learningNarrative inquiry

Abstract

fetched live from OpenAlex

While Aboriginal youth mentoring has been used as a teaching process for thousands of years and the tradition continues, little attention has been paid to documenting what elements make learning experiences transformational. As part of the evaluation of the Aldara Yenara mentoring program, this Aboriginal-led scoping review examined literature about transformational mentoring programs from Canada, Australia and Aotearoa New Zealand to understand their key elements and provide guidance for future research and practice. The use of relational mapping was applied in an attempt to locate literature written by Aboriginal scholars including grey literature. Twenty-seven documents were reviewed including 20 from the peer-reviewed literature and seven acquired through the relational mapping. A total of 13 met the inclusion criteria, predominantly written by non-Aboriginal authors. Four distinct themes emerged and informed our narrative synthesis. Absent in this material, largely neither led nor owned by Aboriginal people, was any reference to connection to Country as central to Aboriginal transformational healing programs. Without Aboriginal leadership, communication and processes in these programs, there was a failure to draw on Aboriginal understandings of healing spaces. From here on in, research and practice in this area must be Aboriginal-led to ensure deeper, Aboriginal-informed understandings for First Nations transformational mentoring programs.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0090.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.308
Teacher spread0.286 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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