On climate change skepticism and denial in tourism
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The period leading to and immediately after the release of the IPCC's fifth series of climate change assessments saw substantial efforts by climate change denial interests to portray anthropogenic climate change (ACC) as either unproven theory or a negligible contribution to natural climate variability, including the relationship between tourism and climate change. This paper responds to those claims by stressing that the extent of scientific consensus suggests that human-induced warming of the climate system is unequivocal. Second, it responds in the context of tourism research and ACC, highlighting tourism's significant contribution to greenhouse gas emissions, as well as climate change's potential impacts on tourism at different scales. The paper exposes the tactics used in ACC denial papers to question climate change science by referring to non-peer-reviewed literature, outlier studies, and misinterpretation of research, as well as potential links to think tanks and interest groups. The paper concludes that climate change science does need to improve its communication strategies but that the world-view of some individuals and interests likely precludes acceptance. The connection between ACC and sustainability illustrates the need for debate on adaptation and mitigation strategies, but that debate needs to be grounded in scientific principles not unsupported skepticism.
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.
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 | 0.002 | 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 | 0.000 | 0.000 |
| 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 it