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Record W4317581875 · doi:10.12689/jmep.2023.1201

Investigating the participation motives of women rugby union players in Canada and Wales

2023· article· en· W4317581875 on OpenAlexaffabout
Ga Hye Kim, Alex McInch, John Kerr

Bibliographic record

VenueJournal of Motivation Emotion and Personality Reversal Theory Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPolitical sciencePsychologyAdvertisingDemographic economicsBusinessEconomics

Abstract

fetched live from OpenAlex

<p> Previous interview research has indicated that women’s rugby union participation is multi-faceted, with most players providing several different motives for getting involved in the sport.The aim of this study was to further examine participation motivation in women’s rugby byreplicating and extending the findings of the earlier research (Kerr, 2021) using a differentapproach to data collection and a larger sample size. Snowball sampling was used to recruitrugby playing female participants. A qualitative study focusing on participant responses toopen-ended questions on participation motivation from an online survey was then undertaken.Thematic analysis was utilized to identify sub-themes and major themes from the data. Thesewere found to be common to both Canadian and Welsh female rugby players. Four majorthemes were identified from the survey data. These were:Intrinsic motivation; Unique culture;Barriers to participation; and Acknowledgment of future generations.These major themessubsumed a number of sub-themes with overlapping characteristics.Empowermentandsenseof challengewere included under the major themeIntrinsic motivation, andcountercultureandstereotypesincluded under the major themeBarriers to participation.The current studyreplicated a number of findings from the original study, but there were two new findings. Thefirst was that some players experienced a strong sense of empowerment through playing rugby.The second was the desire to give something back and help to continue to grow the sport.Reversal theory was used to interpret the findings and explain the psychological background tothe players’ participation motives. </p>

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
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 science0.0000.000
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 head0.099
GPT teacher head0.347
Teacher spread0.248 · 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 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

Citations4
Published2023
Admission routes2
Has abstractyes

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