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Record W3016967412 · doi:10.18060/23385

Innovating Youth Tournament Schedules to Minimize School Absenteeism

2020· article· en· W3016967412 on OpenAlexaffabout
Chris Chard, Daniel Wigfield, Luke R. Potwarka

Bibliographic record

VenueSports Innovation Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Substance Use and School Attendance
Canadian institutionsUniversity of WaterlooBrock University
Fundersnot available
KeywordsTournamentAttendanceAbsenteeismSalientPsychologyApplied psychologyDemographic economicsPolitical scienceSocial psychologyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Participation in sport has been lauded for the myriad benefits provided to youth who engage. Similarly, attendance in school has been identified as a salient contributor to academic success. Thus, the purpose of the present study was to explore the extent to which participation in youth representative (“rep”) hockey in Ontario contributes to avoidable absences from traditional school contexts. Specifically, empirical data from 104 youth rep hockey tournaments, ranging from AE-AAA competitive levels, and the Tyke (7-year-olds) to Midget (17-year-olds) age ranks, were utilized to meet the study’s first purpose. The second purpose was to present an alternative and innovative way youth sport tournaments could be scheduled to minimize school absenteeism. The results of the current investigation show there is merit to the proposed shift in tournament scheduling. Specifically, more than 42,000 avoidable school absences, from the 104 tournaments sampled, could be mitigated with a simple adjustment to tournament schedules.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.321
Teacher spread0.249 · 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 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

Citations4
Published2020
Admission routes2
Has abstractyes

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