Nature-Based Tourists in the Gironde Estuary: Examining and Identifying the Relationship between their Expenditure and the Motivations for their Visit
Bibliographic record
Abstract
This paper is a first attempt to investigate the effect of motivations, trip characteristics and the socio-demographic characteristics of tourists on their daily expenditure in the Gironde estuary. The paper examines the effect of these factors by adopting a quintiles regression and an OLS regression. Mainly the quintile regression allowed us to establish a segmentation approach into light, medium and heavy spenders. The empirical results indicate a significant relationship between the importance attached to perform a seaside tourism experience by tourists and their daily expenditure on a current trip. Surprisingly, these results contrast with the fact that the variable reflecting whether or not tourists have already visited a natural amenity appears to have no influence on the level of daily expenditure by tourists. The investigation additionally finds that travel motives, though to a lesser degree, when taken in tandem with variable such as household income, mean of accommodation chosen by tourists influence touristsÕ daily expenditure.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".