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Record W4381623765 · doi:10.1123/iscj.2022-0091

Reflections on Improving Women’s Experiences of Mentorship in Canadian Coaching

2023· article· en· W4381623765 on OpenAlexaffabout
Sara Kramers, Corliss Bean, Caroline Hummell, Veronica Allan, Andrea Johnson, Jennifer Turnnidge

Bibliographic record

VenueInternational Sport Coaching Journal · 2023
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsQueen's UniversityYork UniversityBrock UniversityUniversity of Ottawa
Fundersnot available
KeywordsMentorshipCoachingThematic analysisReflexivityMedical educationPsychologyQualitative researchPedagogyMedicineSociologySocial science

Abstract

fetched live from OpenAlex

Despite recent advancements for women in leadership roles, women remain underrepresented in sport coaching contexts. Mentorship has been advocated as a potential avenue for advancing and sustaining the careers of women coaches. In line with this, national sporting bodies have implemented mentorship programs to pair new and aspiring women coaches with senior leaders. While recent evaluations show promising results, research is needed to understand how these programs are conceptualized, implemented, and experienced by program participants. The purpose of this study was to qualitatively explore stakeholders’ experiences in two Canadian women in coaching mentorship programs. Perspectives were gathered from 21 Canadian sport stakeholders that included program mentees, mentors, and staff. Data were analyzed using a reflexive thematic approach. Findings demonstrate the need for purposefully recruiting both mentor and mentee coaches to sustain meaningful partnerships. Additionally, participants highlighted the need for sport organizations to situate women in coaching as a priority and engage in sponsorship and long-term planning for sustaining women’s advancements in coaching. This study explores women in coaching mentorship programs from multiple perspectives, which may inform future formalized mentorship opportunities for women coaches by addressing identified challenges and barriers.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.397
Teacher spread0.350 · 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 designObservational
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

Citations5
Published2023
Admission routes2
Has abstractyes

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