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Record W3195015154 · doi:10.1108/sbm-02-2021-0013

So you want to work in sports? An exploratory study of sport business employability

2021· article· en· W3195015154 on OpenAlexaff
David Finch, Norm O’Reilly, David Legg, Nadège Levallet, Emma Fody

Bibliographic record

VenueSport Business and Management An International Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of GuelphMount Royal University
Fundersnot available
KeywordsEmployabilityCredentialOriginalityValue (mathematics)PsychologySample (material)Exploratory researchWork (physics)Public relationsSet (abstract data type)MarketingMedical educationManagementSociologyBusinessPolitical scienceEngineeringPedagogySocial psychologyComputer scienceSocial scienceEconomicsMedicineCreativity

Abstract

fetched live from OpenAlex

Purpose As an industry, sport business (SB) has seen significant growth since the early 2000s. Concurrently, the number of postsecondary sport management programs has also expanded dramatically. However, there remain concerns about whether these programs are meeting the demands of both employers and graduates. To address these concerns, this study examines the credential and competency demands of the SB labor market in the United States. Design/methodology/approach Researchers conducted an analysis using a broad sample of employment postings ( N = 613) for SB positions from two different years, 2008 and 2018. Findings Results support that a complex set of SB qualifications exist, and the credentials and competencies included in SB employment postings have evolved over the past decade. Originality/value A noteworthy finding is that meta-skills are found to be particularly important for employability, including items such as communication, emotional intelligence and analytical thinking and adaptability.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.034
GPT teacher head0.316
Teacher spread0.282 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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