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Record W7132974118

Exploring Contingent Self-Worth and the Transition to First Year Varsity Sport

2024· dissertation· W7132974118 on OpenAlexaboutno aff
Chloe Ellard

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisAthletesNarrativeTransition (genetics)Sport psychologyNarrative inquiry
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this longitudinal case study was to explore athletes’ transitions from highschool to varsity sport and self-worth during the transition. Seven fall sport athletes (5 females, 2 males) from four different Ontario universities completed three narrative interviews over their first sport season. Results of thematic and structural narrative analysis demonstrated that fall sport athletes experienced multiple transitions over their first semester of university. Additionally, transition experiences were influenced by identity, social support, and performance. Athletes’ self-worth was threatened when sport, academic, or social relationships were unstable or unsuccessful. Previous experiences with adversity before varsity sport reduced the impact of setbacks or external validation on self-worth. This project provides information on how contingent self-worth influences varsity athlete transitions and provides applied information for coaches and university administration to support athlete well-being during the transition for first year varsity athletes.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.346
Teacher spread0.294 · 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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