MétaCan
Menu
Back to cohort
Record W3184604119 · doi:10.25234/pv/12899

PROFESIONALNI SPORT U REPUBLICI HRVATSKOJ ZA VRIJEME COVID-19 KRIZE: FROM A THREAT TO AN OPPORTUNITY FOR A BETTER STATUS OF PROFESSIONAL ATHLETES

2021· article· en· W3184604119 on OpenAlexaff
Vanja Smokvina, Patricia Ribarić Smokvina

Bibliographic record

VenuePravni vjesnik · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsCanarie
Fundersnot available
KeywordsRemunerationFootballPromotion (chess)AthletesCroatianLeagueRevenueThe RepublicPolitical scienceGovernment (linguistics)BusinessCoronavirus disease 2019 (COVID-19)Sport managementPublic relationsFinanceLawPoliticsMedicinePhysical therapyTheology

Abstract

fetched live from OpenAlex

The paper aims at analysing Croatian professional sport and the impact of the COVID-19 crisis on it. Football was taken as a model for other team sports because of the share of professional sports clubs in the Republic of Croatia in football. In addition, the legal framework set in football may apply to other sports for successfully developing a similar pattern. The analyses are conducted into the revenues (sponsorships, ticketing and TV rights), and expenses (expenses on behalf of players remuneration) of the football clubs in the First Croatian Football League, providing an overview of the professional status of sports clubs, athletes and coaches. It also encompasses an analysis into measures taken by the Government of the Republic of Croatia to support Croatian sport during the COVID-19 crisis. The COVID-19 crisis has been taken as a possible starting position for better regulation of sports in future, especially as regards the professional sports in the Republic of Croatia contributing significantly to the promotion of the Republic of Croatia worldwide.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.148
GPT teacher head0.435
Teacher spread0.287 · 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.

Study designNot applicable
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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePravni vjesnikSame topicSport and Mega-Event ImpactsFrench-language works237,207