MétaCan
Menu
← Back to cohort
Record W7133018662

Athletes' Perceptions of Pre-game Rituals in Open-skill Sports

2020· dissertation· W7133018662 on OpenAlexfundno aff
Devin Bonk

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsnot available
FundersInstitut National du Sport, de l'Expertise et de la PerformanceSocial Sciences and Humanities Research Council of Canada
KeywordsAthletesPerceptionPhenomenonSport psychologyPerspective (graphical)Qualitative research
DOInot available

Abstract

fetched live from OpenAlex

Performance rituals have long been a topic of study in sport psychology. However, previous research has focused on closed-skill tasks and employed methodologies that make it difficult to capture athletes’ perspectives of these behaviours. The purpose of this study was to explore the perceptions of open-skill sport athletes regarding their performance rituals. Nineteen high-performance athletes participated in semi-structured interviews. Interview transcripts were thematically analyzed. Participants described their perceptions of the structures and functions of their performance rituals. These findings contribute to a more nuanced understanding of how athletes perceive their performance rituals. Exploring this phenomenon through a critical-realist lens allowed for the relevant components of pre-existing theoretical representations of rituals to be compared to the lived experiences of the athletes who engage in them.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.451
Teacher spread0.403 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueTSpace→Same topicSport Psychology and Performance→French-language works237,207→