Volonté à payer (VAP) pour la réduction des émissions de dioxyde de carbone au Québec et valeur récréative du parc du Mont-Bellevue (PMB) de Sherbrooke : trois essais en évaluation non marchande
Bibliographic record
Abstract
This thesis is divided into three chapters. The first chapter examines the consumer-citizen duality in two contexts of solar fuel purchase in Quebec. To this end, we conducted an online survey by randomly assigning two questionnaires to two groups of respondents. The first group of respondents (consumer group) was subjected to a consumer scenario based on the decision to buy solar fuel, and the second group (citizen group) was subjected to a scenario based on the decision to sup- port the Quebec government’s renewable energy policy. Using the multi-attribute choice method, we obtained four attributes of solar fuel, namely environmental performance, fuel mix, fuel accessibility, and solar fuel price. We found that citizens are willing to pay CAD $1.96 per liter to reduce 1 % of CO2 emissions, while consumers are only willing to pay CAD $1.36 per litre. Specifically, citizens are willing to pay CAD $122.5/tCO2, while consumers are willing to pay only CAD $82.25/tCO2. Similarly, they are willing to pay CAD $2.19 per liter to increase the share of solar fuel in gasoline by 1 %. In contrast, consumers are only willing to pay CAD $ 1.6 per liter. In terms of accessibility, citizens are willing to pay CAD $1.23 per liter to increase the share of conventional service stations dispensing solar fuel by 1 %, while consumers are only willing to pay CAD $1.12 per liter. These results confirm the literature according to which citizens express higher willingness-to-pay (WTP) than consumers. In addition, people belonging to Quebec’s left-wing parties such as the Parti libéral du Québec, Québec solidaire, Parti québécois, Parti vert and Nouveau Parti démocratique du Québec are more sensitive to environmental issues. This is in line with the literature according to which supporters of more left-wing political parties are often more respectful of the environment. In the second chapter, we evaluated the effect of policy consequentiality on willingness-to-pay (WTP) in two different contexts : a consumer context based on the decision to buy solar fuel and a citizen context based on the decision to guide the Quebec government in its renewable energy expansion policy. To do this, we conducted an online survey between March 15 and April 08, 2021 among people aged 18 and over, who have at least one internal combustion engine vehicle, and who reside in the province of Quebec. This is the same survey as in Chapter 1. To answer our research question, we designed two versions of the questionnaire, randomly assigned to respondents. We used the random parameter logit model to assess the effect of policy consequentiality on respondents’ WTP for solar fuel at- tributes (environmental performance, accessibility and fuel mix). The results show that consequential individuals in the consumer group are willing to pay CAD $106 to reduce one tonne of CO2, while non-consequential consumers are only willing to pay CAD $16 per tCO2. Similarly, consequent citizens are willing to pay CAD 159 to reduce a tonne of CO2, while non-consequent citizens are only willing to pay CAD 3.44 per tCO2. The results are in line with the literature according to which a strong perception of policy consequentiality increases respondents’ willingness to pay (WTP). Analyzing both samples, we find that consequential individuals subject to the public policy context express higher WTPs than consequential individuals subject to the private consumption context. The third chapter evaluates the demand for recreational visits to PMB in summer and winter. To do this, we conducted two online surveys (summer and winter) of visitors to Mont-Bellevue Park (PMB). The demand for recreational visits and their values are estimated using the travel cost method (TCM) and the truncated negative binomial model (TNBM). Travel cost is an important determinant of demand for recreational visits to the park. The lower the travel cost, the higher the demand for visits, and vice versa. We found an annual consumer CS of CAD $553,168 in summer and CAD $250,985 in winter. This result verifies our hypothesis that the recreational value of Mont-Bellevue Park (PMB) is higher in summer than in winter.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".