The controversy of transferring the Class Environmental Assessment process to northern Ontario, Canada: the Victor Mine Power Supply Project
Bibliographic record
Abstract
Since Canada employs a federated system of government, there are separate environmental assessment (EA) processes at the national and provincial levels. In the Province of Ontario there is a streamlined, pre-approved, self-assessed process for ‘classes’ of projects. It is assumed that Class EA protocol developed in the southern Ontarian context is directly transferable to northern Ontario. A case-based approach, using the Victor Mine transmission line project, was employed to critically examine whether the Class EA template developed in southern Ontario should be applied to the western James Bay region of northern Ontario. Specifically, the two assumptions of Class EAs of predictability and manageability were examined. Interview and document data were used to inform a themed analysis. Results indicate that the western James Bay region is significantly different to southern Ontario. Thus, the Class EA template developed in and for southern Ontario is not transferable to the northern Ontarian context and the application of ‘cookie cutter’ EAs to other sub-arctic and arctic regions must be questioned.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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 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".