Sensitising Green Criminology to Procedural Environmental Justice: A Case Study of First Nation Consultation in the Canadian Oil Sands
Bibliographic record
Abstract
Procedural environmental justice refers to fairness in processes of decision-making. It recognises that environmental victimisation, while an injustice in and of itself, is usually underpinned by unjust deliberation procedures. Although green criminology tends to focus on the former—distributional dimension of environmental justice—this article draws attention to its procedural counterpart. In doing so, it demonstrates how the notions of justice-as-recognition and justice-as-participation are jointly manifested within its conceptual boundaries. This is done by using the consultation process that occurs with indigenous peoples on proposed oil sands projects in Northern Alberta, Canada, as a case study. Drawing from ‘elite’ interviews, the article illustrates how indigenous voices have been marginalised and their Treaty rights misrecognised within this consultation process. As such, in seeking to understand the procedural determinants of distributional injustice, the article aims to encourage broader green criminological scholarship to do the same.
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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 | 0.001 | 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) | 0.000 | 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".