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Record W2479406351 · doi:10.1123/cssm.2014-0032

An Age-Old Problem in Little League Baseball

2015· article· en· W2479406351 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCase Studies in Sport Management · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransportation Systems and Infrastructure
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsLeagueAthletesPsychologyPublic relationsPolitical sciencePhysical therapyMedicine

Abstract

fetched live from OpenAlex

The relative age effect (RAE) has become a well-studied consequence of organizations utilizing a cutoff date to establish age cohorts. Within this case study, students will explore and learn how to perform various statistical analyses (i.e., chi-square, effect sizes, standardized residuals) to determine whether the RAE exists among those who competed in the 2011 and 2012 Little League World Series (LLWS). Students will learn about the mission and history of Little League Baseball (LLB) and discuss potential changes and/or strategies that could be used by the organization to make the LLWS more inclusive. Furthermore, students can use the knowledge gained from this case study to critically analyze the current status of various other sport organizations to help develop potential strategies to ensure fairness and equality for all participating athletes.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.286
Teacher spread0.244 · 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