Essays on the economics of reclamation: Optimization, preferences, and validity
Bibliographic record
Abstract
Extractive activities are an important economic sector in many countries worldwide and most jurisdictions have regulations to secure land restoration to an adequate post-extractive state. The reclamation process, which aims to return the affected area to a state that is the same or similar the one found before the activities began, is guided by public policy that aims to restore landscapes, recover natural resources, and address adverse effects (e.g. negative externalities) created by extractive activities like mining and oil and gas extraction. This thesis presents three studies to analyze the potential costs and benefits of reclamation policies, with a particular focus on water quality and time required to complete reclamation. The first two papers examine the case of oilsands mining in northern Alberta – an economically important industry in Alberta and Canada where reclamation targets for water quality have yet to be determined. The first paper implements a mathematical programing model to estimate the effects of different water quality targets for treated Oil Sands Processed Water (OSPW) on the treatment cost and other reclamation variables for mining firms in Northern Alberta. This model demonstrates the sensitivity of treatment costs, time required for treatment, and choice of technology to different water quality targets. These findings show that defining a standard for treated OSPW could have significant economic consequences to the mining companies in Northern Alberta. This paper also provides information on the marginal abatement costs for alternative treatment technologies. The second paper explores the public preferences for different reclamation policies for OSPW in Alberta. The benefits of alternative water quality targets are non-market in nature requiring the use of stated preference approach to economic valuation. Stated preference methods can be affected by a number of potential biases. We develop a theoretical framework to analyze how the use of Inferred Valuation (IFV), which is used to capture the Social Desirability Bias (SDB) of participants, is influenced by the perceived income similarities to the reference group. By using a willingness to pay (WTP) and willingness to accept (WTA) survey we asses the validity of the IFV method. We find evidence of SDB in our sample and our results show that perceived income similarities influence the inferred WTP and WTA. However, the direction of the effect of these perceived similarities does not always conform with our theoretical expectations. To complement this study, the third paper examines the criterion validity and the usefulness of follow-up certainty statements (FCS) to control for differences in hypothetical and real scenarios in a referendum experiment using the participant’s time as the good being valued. We also explore follow-up questions aimed to identify SDB that might affect responses in experimental settings. Our results are consistent with the stated preference literature and show that FCS help reduce the gap between hypothetical and real scenarios for a single binary choice (SBC) question in a WTA context. Together these studies not only give insight to the design of policies oriented to incentivize the reclamation of OSPW, but also contribute to the stated preference literature by testing the validity of methods that may be able to improve welfare measurement related to changes in environmental goods and services.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".