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Record W3209230270 · doi:10.11575/prism/39211

Indigenous Mentorship for the Health Sciences

2021· dissertation· en· W3209230270 on OpenAlexaboutno aff
Elaine J. Atay

Bibliographic record

VenueOpen MIND · 2021
Typedissertation
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsMentorshipIndigenousBiomedical sciencesMedicinePolitical scienceLibrary scienceSociologyMedical educationBiologyNursingComputer scienceEcology

Abstract

fetched live from OpenAlex

The present study aimed to establish the credibility and attributed outcomes of an existing Indigenous mentorship (IM) model from the perspective of Indigenous mentees in health sciences and community research. Six mentees from mentorship networks associated with the Canadian Institute of Health Research’s IM Network Program participated in 1-2 hour long semi-structured interviews inquiring: 1) their resonance with the IM model, 2) personal stories related to the behavioural constructs in the model, 3) outcomes their mentors’ behaviours had on them, and 4) components they felt were missing from the model. Overall, the model resonated with participants. Of the model constructs, mentees discussed mentor behaviours associated with practicing relationalism the most frequently (26%), followed by fostering Indigenous identity development (23%), mentee-centered focus (21%), and imbuing criticality (16%). Advocacy (9%) and abiding by Indigenous ethics (5%) were addressed, but not given as much attention as the other constructs. Outcomes included positive career and work attitudes, engaging in more helping behaviours, motivation, overall well-being, and enhanced criticality. Recommendations to expand the model included incorporating: 1) additional mentor behaviours (transference of traditional knowledge, prayer, modeling resiliency, and engaging in trauma-informed practices), 2) higher-order dimensions (e.g., institutional impact), 3) specific mentee characteristics (e.g., age and gender), and 4) additional types of mentoring relationships (e.g., peer, multiple mentors). This research provides valuable insight to the IM model and IM theory more generally. This information can be applied to refine culturally appropriate mentorship practices, mentor selection and support, and evaluation of mentorship 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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.696
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.417
GPT teacher head0.627
Teacher spread0.211 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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Same venueOpen MINDSame topicHealth Sciences Research and EducationFrench-language works237,207