National tourism organizations and climate change
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
There is a consensus that the global tourism system needs to undergo decarbonization and achieve net-zero emissions by mid-century. However, given the anticipated growth in the most energy-intensive subsector of tourism, air transport, achieving this goal seems unlikely. This paper focuses on the role of distance in the global geography of tourism, against evidence that National Marketing Organizations (NTOs) often seek to attract visitors from all over the world. The analysis of data for a sample of 12 NTOs in Europe, the USA and Canada reveals that the number of markets targeted varies between six and 33, with significant differences in the average distance to markets (<4,000 to 8,000 km), as well as emissions per arrival by market (0.2 t CO2 to 2.5 t CO2). For the countries studied, the 17% of the most distant arrivals cause 62% of the emissions. Results also show that more distant markets are more sensitive to disruptions such as COVID-19. These findings have relevance for destination marketing that point to new climate change related roles for NTOs such as rebranding, demarketing, market segmentation, and communication.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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