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Record W4386543077 · doi:10.1590/rbce.45.e20230022

University sport and scholarship funding for student-athletes: possibilities and limitations to sports performance

2023· article· en· W4386543077 on OpenAlexaboutno aff
Alex Caiçara de Albuquerque, E Costa, Da Silva

Bibliographic record

VenueRevista Brasileira de Ciências do Esporte · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPhysical Education and Sports Studies
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsScholarshipAthletesQuarter (Canadian coin)InstitutionPolitical scienceMedical educationValue (mathematics)SociologyPublic relationsMedicinePhysical therapyHistoryLaw

Abstract

fetched live from OpenAlex

ABSTRACT The study investigated the policy of funding sports scholarships to student-athletes linked to the Federal University of Mato Grosso do Sul, Brazil. This is exploratory and documentary research, with an analysis of the opening and results edicts of the Athlete Scholarship Program (2010-2021). The institution has the Athlete Scholarship Program. Scholarships were paid R$400.00, with an annual duration of 9 and 7 months, with emphasis on individual sports, especially wrestling, athletics, and swimming. It is concluded that the university presents a policy that favors the sport of institutional representation, however, not the high performance, given the low value of the scholarship and the non-payment of it in the first quarter of all the years analyzed.

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)0.026
metaresearch head score (Gemma)0.084
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 score0.031
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.084
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0020.004
Scholarly communication0.0070.003
Open science0.0020.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.075
GPT teacher head0.346
Teacher spread0.271 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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