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Record W2743631014

Friend, foe, or both? A retrospective exploration of sibling relationships in elite youth sport

2015· article· en· W2743631014 on OpenAlexaff
Kendra S Nelson, Leisha Strachan

Bibliographic record

VenueMspace (University of Manitoba) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of ManitobaWestern University
Fundersnot available
KeywordsSiblingElitePsychologySibling relationshipAthletesDevelopmental psychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

With the abundance of literature focusing on parental influence in sport, it is important to identify family dynamics that extend beyond parents to include siblings. Research indicates that siblings have the potential to influence social, behavioral, and cognitive development across various achievement domains (Brody, 1998). In this study, sibling influence was explored though semi-structured interviews with previously identified elite youth athletes (N=4) and their sibling who participated in the same sport (N=4). Using a grounded theory and retrospective approach, the purpose was to discover how siblings influence elite youth sport participation. After data analysis of the two groups, two main categories emerged from the data: positive experiences participating in the same sport (e.g., growth of sibling relationship, development of understanding between siblings) and negative experiences participating in the same sport (e.g., sibling competition, emotional response). The participants' descriptions coincide with observational learning theory (Mischel, 1966) and both deidentification (Ansbacher & Ansbacher, 1956) and divergence processes (Darwin, 1859; Sulloway, 1996). The data adds to the probable sibling experiences proposed in the Developmental Model of Sport Participation (Fraser-Thomas, Strachan, & Jeffery-Tosoni, 2013) and provides insight and suggestions for athletes, parents, and coaches on how to best manage sibling relations in sport.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.113
GPT teacher head0.270
Teacher spread0.157 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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