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Record W7026603233

Acimowina: Indigenous Women Leaders Telling Stories

2024· dissertation· en· W7026603233 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2024
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
Fundersnot available
KeywordsMentorshipIndigenousLeadership developmentStorytellingQualitative researchFocus groupTransformative learningLeadership studies
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT\nThis dissertation explored the role of mentoring in Indigenous women’s leadership in education. This abstract introduces the problem of practise, the purpose of the study, research methods used, findings and conclusion.\nProblem of Practice: While Indigenous women have increasingly accessed educational opportunities and leadership positions, they remain underrepresented in leadership roles. The consequence of this slow growth is the lack of role models to mentor Indigenous women along their leadership journey. The problem of practice I sought to explore was how mentoring had contributed to Indigenous women’s growth as leaders. \nPurpose of Study: The purpose of this study was to establish the role of mentorship in the grow of Indigenous women leaders. I conducted this inquiry through engaging in conversations with Indigenous women who have held leadership roles in education administration. The larger inquiry question that guided this study was: How have culture, community, opportunities or challenges, and mentorship supported Indigenous women in their leadership roles? Additional guiding sub questions included:\n§ How had culture and community informed their roles as Indigenous woman leaders?\n§ How had opportunities or challenges impacted their leadership journey?\n§ How had mentorship influenced their leadership journey?\n§ What insights did these Indigenous leaders hope to leave to other Indigenous women in order that other might realize their leadership potential?\nMethods: This study used qualitative approaches to gather rich descriptions of Indigenous women’s stories about their leadership experiences and the role that mentorship had played in their journeys. The study was conducted using methods found within storytelling methodology including conversations within a Kiyokewin (visiting) practise guided by semi-structured interview questions. This method was chosen for its alignment with Indigenous research paradigm and practice. This approach embraced the importance of relationality (Wahkohtowin) as a key practice in Indigenous research and in Kiyokewin. The study involved five participants (who have been educators) and who had lived in Treaty 4, 6, and 7 areas of Saskatchewan and Alberta. Purposive sampling was used in the selection of participants. \nFindings: Indigenous women leaders are an understudied group; it is anticipated that the findings will move knowledge forward by discussing the importance of mentoring to leader growth and retention. \nConclusion: Indigenous women were influenced by family matriarchs—mothers, grandmothers, sisters, aunties—as mentors and supporters in their leadership journeys. \nPractice Implications of Inquiry: The study findings contributed to knowledge on Indigenous women in leadership and the role of mentoring to support leadership.

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)0.007
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0200.010
Scholarly communication0.0070.008
Open science0.0020.008
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.178
Teacher spread0.165 · 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 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
Published2024
Admission routes1
Has abstractyes

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