Climate change risk in the Swedish ski industry
Bibliographic record
Abstract
Tourism industry and government demand for knowledge of the impacts of climate change on ski tourism is growing. Despite the more than 70-year history and large cultural significance of alpine skiing in Sweden, little is known about the industry’s future under a changing climate. This study applies the SkiSim2 model with low to high emission scenarios (RCP2.6 to 8.5) to analyse the implications of climate change for ski operations (season length, snowmaking requirements) at 23 alpine ski areas across Sweden for the early, mid and late twenty-first century. Northern areas of Sweden show much less reduction in average season length compared to central and southern Sweden under the high emission mid- (13% versus 58% and 81%) and late-century scenarios (27% versus 72% and 99%). To limit season losses in these scenarios, snow production increases of over 250% are required in all regions. Such increases will create additional financial and environmental stressors, which may lead to the closure of the most at-risk resorts. With greater impacts projected for much of the European Alps ski market, northern Sweden may represent a ‘last resort’ for the European ski industry under higher emission scenarios by the mid-late twenty-first century.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".