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Record W2620888717

학생선수들의 수업결손에 대한 정책대안연구

2004· article· ko· W2620888717 on OpenAlexaboutno aff
이상연, 안민석

Bibliographic record

Venue한국체육학회지 · 2004
Typearticle
Languageko
FieldMedicine
TopicDiverse Approaches in Healthcare and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPrestigeBasketballEliteAppealAthletesQuarter (Canadian coin)PsychologyIdeologySport managementGrassrootsPolitical sciencePublic relationsAdvertisingBusinessMedicineLawGeography
DOInot available

Abstract

fetched live from OpenAlex

Koreans, have utilized sports to gain prestige into international community and to save propaganda an ideological purposes until the 88 Seoul Olympic Games, and it had very strong elits sport system. A balanced development of elite sports and grassroots spurts, however, has been a critical issue. The academic achievement of the student-athlete in Korea is a currently hot issue. The public is aware of the potential problems regarding the quality of education that student-athlete receive through the efforts of muck-raking joumalists and ex-athletes. There doesn`t appeal to be a positive relationship between athletic participation and academic performance at the school level. Also, the administrative authority responible for policing the athletic programs of student-athlete is likely to neglect the investigation of charges that athletes may be raeiving inferior educations. That the paper identified the level of school-absence for the student-athlete and analyzed the problem based on different sport such as baseball, soccerball and basketball. In conclusion, the paper provided some directions for reforming the system of the school elite-sport: abolishing the quarter and semi-quarter system, considering the academic record for college enterance, establishing the matches at weekend and vacation instead of workday and so on.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.005

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 head0.120
GPT teacher head0.372
Teacher spread0.252 · 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; both teacher heads agree on what is shown here.

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
Published2004
Admission routes1
Has abstractyes

Explore more

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