So you want to work in sports? An exploratory study of sport business employability
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".