해외올림픽 레거시 창출 사례의 2018 평창 동계올림픽에의 시사점 - 2010 밴쿠버 동계올림픽과 2012 런던 하계올림픽 사례분석을 중심으로 -
Bibliographic record
Abstract
The purpose of this study was to make suggestions for policy development of legacy creation for the 2018 PyeongChang Winter Olympic and Paralympic Games. In order to achieve this purpos of the study, two previous cases of olympic legacy creation, 2010 Vancouver Winter Olympic and Paralympic Games and 2012 London Summer Olympic and Paralympic Games, were reviewed. Based on the findings of the case study, experts meetings were held for the purpose of drawing the suggestions. As the results of this study, three implications were suggested. Firstly, the approach to the olympic legacy creation for PyeongChang 2018 has to be clarified and this approach should be presented in the games` legacy vision and action plan. Secondly, it is necessary to establish an organization exclusively responsible for legacy development and delivery, in order to ensure the effectiveness and sustainability of the games` legacy. Finally, it is required to encourage the local government of the host area involvement and private sector participation in the games` legacy creation and delivery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".