Bibliographic record
Abstract
This paper shows that it is difficult, if not impossible, to formulate policies that guarantee that tourism can be maintained for a long time without severely impacting on the environment. The analysis is purely theoretical and is based on very simple and general assumptions about the interactions between the three main components of the system: the tourists, the environment, and the capital. These assumptions are encapsulated in a so-called minimal model, used to predict the economic and environmental impact of any given policy. This paper is of value for three reasons. First, it introduces the approach of minimal descriptive models in the context of tourism, which has traditionally been dominated by the use of black-box econometric models. Second, the specific results are quite interesting. We show, in fact, that tourism sustainability can be achieved, provided agents are prudent about reinvesting their profits and are willing to protect the environment, but that sustainability is very often at risk, because unforeseen shocks can easily trigger a switch from a profitable and compatible behavior to an unprofitable or incompatible one. These results are in line with conventional wisdom and observations, but the interesting fact is that here they are theoretically derived from a few very simple and abstract premises. Third, although not directly related to the problem of tourism but rather to the general topic of sustainability, this is one of the first times that the notion of sustainability, which is more and more pervasive in the field of resource management, is interpreted strictly in terms of the structural properties of the attractors of a dynamic system. This creates an important and promising bridge between sustainability and bifurcation theory, one of the most important areas of systems analysis.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".