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Record W2810758132 · doi:10.5430/ijhe.v7n4p17

Determination of the Perceptions of Sports Managers About Sport Concept: A Metaphor Analysis Study

2018· article· en· W2810758132 on OpenAlexvenueno aff
Serkan Kurtipek, Uğur Sönmezoğlu

Bibliographic record

VenueInternational Journal of Higher Education · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsMetaphorSport managementPerceptionContent analysisPerspective (graphical)PsychologyQualitative researchApplied psychologySociologyPublic relationsSocial scienceComputer sciencePolitical science

Abstract

fetched live from OpenAlex

The aim of this research is to determine the perceptions of sport managers in Turkey on the concept of sport by means of metaphors. 74 sport managers participated in the research. Phenomenology, one of the qualitative research methods, was used in the research. Content analysis method was used for the data analysis. Evaluation of the data showed that sports managers produced a total of 50 metaphors. These metaphors produced were collected in 6 different categories. As a result, it was determined that sport managers expressed the concept of sport by means of metaphors in a very rich and diverse perspective. Therefore, the metaphors determined in this study may lead the sport managers and candidates responsible for the administration of sports services and activities in terms of offering a different perspective on the practice of sport management.

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)0.006
metaresearch head score (Gemma)0.008
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 score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.350
Teacher spread0.323 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

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