Climate Resilience of Arctic Tourism: A Finnish Perspective on the Post-Paris Agreement Era
Bibliographic record
Abstract
The Arctic is more globalised than ever and, in the Anthropocene, the Arctic region should be recognised as the laboratory of the future of industrial civilization (GlobalArctic, 2020). The actions taking place in the Global Arctic today may indicate how climate change impacts our future (see Finger & Heininen, 2019). Therefore, an analysis of the Arctic can provide a ‘road map’ for the post-Paris Agreement era (see Wu et al., 2018). In the Arctic, where the effects of climate change are the strongest, we see the importance of climate resilience, a concept highlighted in the Paris Climate Agreement. Arctic tourism in Finland is an illustrative example of climate resilience, as the industry has to respond to many different changes at the same time. Finland’s government has set the goal of achieving carbon neutrality as the first industrialised society in the world by 2035. Global warming and the changing business environment is increasing the vulnerability of the tourism industry. Simultaneously, dramatic impacts following COVID-19 restrictions may halt the first-rate success of this locally essential livelihood. Unless we are able to effectively coordinate efforts to develop climate resiliency, the implementation of necessary measures will be delayed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".