Bibliographic record
Abstract
2023 was a landmark year for climate change, with hundreds of climate records broken around the world concurrent with the conclusion of the IPCC Sixth Assessment (AR6) process and the first United Nations (UN) Stocktake on climate action. This special issue builds on the AR6 with three papers on key global tourism and climate change knowledge gaps (tourism and climate policy integration, pathways to deep emission reductions, tourism demand) and nine in-depth assessments of tourism climate and carbon risk in each of the IPCC regions. These important contributions of 65 different authors from 30 countries also supported the first ever global stocktake of climate action in the tourism sector. The papers in this special issue make clear that global tourism as we know it in the early twenty first century will be transformed by the climate crisis. Based on the collective contributions, this introduction to the special issue summarizes the state of tourism and climate change research, sets out a research agenda related to the low carbon transition, adapting to accelerating climate disruption, and climate justice, and emphasizes the urgent need to mobilize the tourism academy in this decisive decade for climate action.
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 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".