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Record W3104785808 · doi:10.1123/cssep.2020-0015

Career Assistance to a Team in Crisis-Transition: An Intervention Case Study in Swedish Elite Handball

2021· article· en· W3104785808 on OpenAlexaff
Johan Ekengren, Natalia Stambulova, Urban Johnson, Andréas Ivarsson, Robert J. Schinke

Bibliographic record

VenueCase Studies in Sport and Exercise Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsLaurentian University
Fundersnot available
KeywordsEliteCoping (psychology)PsychologySport psychologyApplied psychologyIntervention (counseling)Perspective (graphical)Medical educationPolitical scienceClinical psychologyMedicinePolitics

Abstract

fetched live from OpenAlex

In this paper, the authors share how a career assistance program was developed, implemented, and evaluated with a Swedish elite handball team. Within this case study, the initial version of the career assistance program’s content was created based on the career-long psychological support services in a Swedish handball framework and the first author’s applied experiences. During implementation, the head coach was terminated unexpectedly, and the team appeared in a crisis. This transitional situation led to modification of the career assistance program to help the players cope with changes. Eighteen players took part in eight workshops dealing with various aspects of their sport and nonsport life (e.g., performance, training, lifestyle, recovery, and future planning) with crisis-related issues (e.g., coping with uncertainty) incorporated. Mixed-methods evaluation revealed the players’ perceived increase in personal resources (awareness and skills) and decrease in stress and fatigue. Reflections on working in applied sport psychology from a holistic perspective in a dynamic real-life setting are provided.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0090.003
Scholarly communication0.0030.001
Open science0.0030.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.063
GPT teacher head0.420
Teacher spread0.358 · 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 designCase report
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

Citations5
Published2021
Admission routes1
Has abstractyes

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