Journalism, Environmental Issues, and Sport Mega-Events: A Study of South Korean Media Coverage of the Mount Gariwang Development for the 2018 PyeongChang Winter Olympic and Paralympic Games
Bibliographic record
Abstract
Few studies on sport and communication consider how environmental issues are reported on—especially in non-Western media. In this article, we report findings from a study of South Korean mainstream and alternative print media coverage of the controversial development of Mount Gariwang for the 2018 PyeongChang Winter Olympic and Paralympic Games. Our study focused on (1) how the decisions and events unfolding around the development of Mount Gariwang were portrayed in South Korean mainstream and alternative news coverage and (2) how the issues at play were politicized and/or depoliticized within and across these outlets. We found that differences in coverage of environmental issues were starkest between, on one side, conservative mainstream media and, on the other side, left-leaning mainstream and alternative media outlets. We also found that environmental controversies were variably politicized or depoliticized in differently positioned media outlets—with left leaning and alternative media highlighting concerns about Olympic-related hypocrisy and corruption, and right-leaning media usually featuring depoliticizing statements from Olympic and government elites. All media outlets highlighted questions about why viable and existing venues were not being used instead of Mount Gariwang, with economic and environmental issues being emphasized differently across outlets. We conclude with reflections on the relevance of our findings for considering links between sport, mediatization, journalism, and environmental politics and suggestions for future research in international coverage of sport- and mega-event-related environmental issues.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".