Evaluating an Environmental Right: Information Disclosure, Public Comment, and Government Decision Making in Ontario
Bibliographic record
Abstract
In 1993, the Ontario government enacted the Environmental Bill of Rights (EBR). The EBR guarantees residents of the province, among other things, the right to comment on permit requests to take water and to discharge into the air and a guarantee that these comments are taken into account in the decision to approve or deny a permit. We model the firm's decision to request a permit, a resident's decision to provide public comment, and the government's decision to approve or deny permit requests to use water or air. Our examination of 1,000 government decisions regarding permit requests leads to two key findings: (1) few permit requests receive any public comment; and (2) to the extent that the public does comment, we find no empirical evidence that comments affect the likelihood that the government will deny a permit request. Our theoretical model anticipates the first result: there are few comments observed for permit applications, because each individual has an incentive to undercontribute to the provision of a public good. The second result did not support the theoretical argument we advance: government, acting to maximize social welfare, takes public concern as a signal of environmental damage. En 1993, le gouvernement de l'Ontario a édicté la Charte des droits environnementaux (CDE). La CDE garantit aux résidents de la province, entre autres, le droit de faire des observations sur les demandes de permis pour puiser l'eau et rejeter des quantités limitées de substances polluantes dans l'air, et garantit aussi que ces observations seront prises en considération dans la décision d'accorder ou de refuser un permis. Nous avons modélisé la décision d'une entreprise de déposer une demande de permis, la décision d'un résident de faire des observations et la décision du gouvernement d'accorder ou de refuser les demandes de permis pour l'usage de l'eau ou de l'air. L'examen de 1000 décisions du gouvernement concernant des demandes de permis a menéà deux principaux constats: 1. peu de demandes de permis reçoivent des observations du public; 2. lorsque le public soumet des observations, aucune évidence empirique ne laisse supposer que les observations influent sur la probabilité que le gouvernement rejette une demande de permis. Notre modèle théorique a anticipé le premier constat: les demandes de permis reçoivent peu d'observations parce que chaque individu a un incitatif à sous–contribuer à la fourniture d'un bien collectif. Le deuxième constat n'a pas appuyé notre argument théorique voulant que le gouvernement, qui agit afin de maximiser le bien–être collectif, tienne compte des préoccupations du public comme un signal de dommage environnemental.
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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 | 0.009 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".