Bill C-69: The Proposed New Federal Impact Assessment Act (IAA)
Bibliographic record
Abstract
In this post, I offer my assessment of what I consider to be some of the key elements of the proposed new federal Impact Assessment Act (the first part of Bill C-69, available at: http://www.parl.ca/DocumentViewer/en/42-1/bill/C-69/first-reading). This post is an effort to put in lay terms how the proposed Act would work, and how it would differ from CEAA 2012.\nI have grouped my assessment of the proposed Act according to the main elements of the process and other key features. There are many cross-cutting and other issues that deserve separate attention, such as public participation, transparency issues, the role of Indigenous peoples, learning, accountability, multi-jurisdictional cooperation, climate change, assessment of projects on federal lands and outside Canada, among others. Addressing these all would have made this post even longer than it already is, and would have significantly delayed its release. I will follow up on some of these issues with separate posts, so stay tuned.
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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.026 | 0.017 |
| Insufficient payload (model declined to judge) | 0.019 | 0.016 |
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".