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Record W3121991888

Do Sports Crowd Out Books? The Impact of Intercollegiate Athletic Participation on Grades

2016· preprint· en· W3121991888 on OpenAlexaboutno aff
Michael Insler, Jimmy Karam

Bibliographic record

VenueRePEc: Research Papers in Economics · 2016
Typepreprint
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsnot available
FundersU.S. Naval AcademyVassar CollegeNorthwestern University
KeywordsAthletesInstrumental variablePromotion (chess)Quarter (Canadian coin)Peer effectsPsychologyRandom assignmentMedical educationPolitical scienceSocial psychologyMedicinePhysical therapyEconomicsGeographyStatisticsEconometricsMathematics
DOInot available

Abstract

fetched live from OpenAlex

We investigate the infl uence of intercollegiate athletic participation on grades using data from the U.S. Naval Academy. Athletic participation is an endogenous decision with respect to educational outcomes. To identify a causal effect, we develop an instrument via the Academy’s random assignment of students into peer groups. Instrumental variables estimates reveal that sports participation reduces athletes’ grades, on average, by nearly one-quarter of a letter grade. This finding has implications beyond college, as we also show that grades--not athletic participation--are most strongly associated with post-collegiate outcomes such as military tenure and promotion rates.

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)0.002
metaresearch head score (Gemma)0.022
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 score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.077
GPT teacher head0.420
Teacher spread0.343 · 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
Published2016
Admission routes1
Has abstractyes

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