The Canadian Impact Assessment Act and intersectional analysis: Exaggerated tensions, fierce resistance, little understanding
Bibliographic record
Abstract
Abstract Canada's newly adopted Impact Assessment Act requires gender‐based analysis plus (GBA+)—a type of intersectionality mainstreaming—as part of assessing the impacts of resource projects. This explicit inclusion of a GBA+ requirement in legislation for the first time represents an important advance in Canada's commitments to mainstreaming, and one that offers an opportunity to examine how interested policy actors both enable and challenge mainstreaming commitments in the legislative sphere. We consider what the compound problem of invisibility and resistance in the legislative process means for ongoing efforts to advance intersectional policymaking and strengthen mainstreaming in Canada and other western democracies.
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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 | 0.087 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.037 | 0.087 |
| Scholarly communication | 0.039 | 0.009 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 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".