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Record W7008802726

Corporate Social Responsibility and Legitimacy Management in Charitable Sport Foundations: Evidence from Major League Soccer Clubs

2024· article· en· W7008802726 on OpenAlexfundno aff

Bibliographic record

VenueCINECA IRIS Institutial Research Information System (University of Genoa) · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
FundersUniversity of ThessalyUniversidade de PernambucoUniwersytet WarszawskiSyddansk UniversitetUniversità degli Studi di PalermoWestfälische Wilhelms-Universität MünsterWaseda UniversityVrije Universiteit BrusselEberhard Karls Universität TübingenUniversity of TorontoUniversity of StirlingUniversity of South AustraliaVictoria UniversityWestern Sydney UniversityUniversity of the West of ScotlandUniversitetet i StavangerForo Italico University of RomeUniversità degli Studi di TorinoTulane UniversityVirginia Commonwealth UniversityUniversity of North TexasWashington State UniversityUniversity of OttawaUniversity of MontanaWestern Carolina UniversityUniversity of Northern ColoradoUniversity of Massachusetts BostonUniversity of WaterlooUniversity of South CarolinaPécsi TudományegyetemUniversity of MinnesotaWoosuk UniversityUniversiteit UtrechtUniversity of North FloridaYonsei UniversityUniversity of MissouriUniversity of West FloridaWake Forest UniversityUniversity of Technology SydneyUniversity of Louisiana MonroeUniversity of Southern MississippiWayne State UniversityUniversity of Westminster
KeywordsLeagueCorporate social responsibilityLegitimacySocial responsibilityFootball
DOInot available

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.007
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.125
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.004
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.134
GPT teacher head0.328
Teacher spread0.193 · 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 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

Citations0
Published2024
Admission routes1
Has abstractno

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