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Record W7079885198 · doi:10.26108/pgw9-5486

Giving back: investigating the motives of female volunteer youth sport coaches

2024· other· en· W7079885198 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2024
Typeother
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsCoachingGrounded theoryObligationFeelingAthletesMeaning (existential)Youth sports

Abstract

fetched live from OpenAlex

Despite the many benefits of youth sport, the recruitment and retention of coaches is an ongoing pervasive issue faced by sport organizations. This lack of coaches is even more prevalent among females when compared to their male counterparts despite the significant increases in females participating in sport. Nevertheless, relatively little research has been conducted on the notion of “giving back” to sport as a coach, particularly with female sport coaches. Therefore, the purpose of this study was to utilize a grounded theory approach to explore the experiences of female coaches to identify key factors that have driven them to contribute to their sport organizations through coaching. Eleven Canadian female youth sport coaches participated in semi-structured interviews to investigate their own youth sport experiences, transition from athletic to coaching role, and current role as a coach. In line with a grounded theory approach, data collection and analysis followed a semi-iterative cycle including theoretical sampling which informed changes to the interview guide based upon previous interviews. Findings show that coaches’ motivations to contribute to sport fall under three categories: 1) deriving meaning from their coaching role; 2) enjoying their position; and 3) feeling moral obligation to give back to sport. These common motivators appear to outweigh common barriers of gender and age that arose as unique to the female experience. Results map onto similar literature as female coaches also strive to be the female role models they once had in sport, and gender stands in the way of many female coaches.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.267
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.031
GPT teacher head0.237
Teacher spread0.205 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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