Évaluation économique de la connectivité écologique du Parc du Mont-Bellevue : une approche par la méthode à choix multi-attributs
Bibliographic record
Abstract
In this work, we address a novel theme: attributing an economic dimension to ecological connectivity, a topic scarcely explored in the field of economic sciences. We use Mont-Bellevue Park as an exploratory field due to its status as an urban park in the city of Sherbrooke. We present two measures of willingness to pay (WTP) through the discrete choice method, namely the Random Parameter Logit (mixlogit) and the Conditional Logit (clogit). Of the two models, we favor the RPL over the clogit, as it resolves the three limitations of the standard clogit by allowing random taste variation, unrestricted substitution patterns, and correlation of unobserved factors over time. The willingness to pay is calculated using a general model, taking into account only the attributes and different levels. We then calculated it considering the types of users (pedestrian activity, cycling, hiking, picnicking, nature observation, and dog walking). The study hypothesis, supported by literature, posits that improving ecological connectivity leads to a higher willingness to pay for Mont-Bellevue Park users. To verify this assertion, an online survey was conducted in the summer of 2022. This survey collected 1,333 responses, of which 813 were admissible as they met the criteria of geographic belonging and frequency of use. We find that the WTP for ecological connectivity in an intermediate situation (which maintains some corridors) and in a good situation (which ensures perfect connectivity between green spaces) are significant and positive at 1%. We note an important result: the variation is positive (377.138 - 217.809 = 159.329). Users are generally willing to pay an additional 159.329 CAD to move from the intermediate connectivity situation to the good connectivity situation. This confirms our hypothesis. Regarding user types, those who engage in pedestrian activities have a WTP variation of 136.881 CAD, nature observers 283.686 CAD, picnickers 400.424 CAD, VTT enthusiasts in the park 223.47 CAD, and dog walkers 95.041 CAD. These results are informative and show that the types of parks use influence the WTP. The overall results suggest that all types of users attribute more monetary value to ecological connectivity as it improves. The WTP is applied in the form of an annual municipal tax and could serve as a reference framework for the city of Sherbrooke and PMB managers in establishing a policy to preserve or improve the compromise between urban development and the protection of ecological integrity.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".