Bibliographic record
Abstract
This paper considers the issue of environmental racism as it relates to Indigenous and Black communities in Canada. Although the climate crisis affects us all, certain communities have felt the effects of environmental degradation more acutely and for a longer period. Environmental policy or practice that disproportionately disadvantages a racial group is an example of environmental racism. The article examines different policy responses to environmental racism in a Canadian context. The paper looks at proposed avenues for addressing environmental racism through the Charter of Rights and Freedoms, Private Members Bills, Senate Bills or the new Federal Housing Advocate position associated with the Canadian Human Rights Commission. It also examines a number of grassroots initiatives taking action against environmental racism. The article argues that having the right to a healthy environment encoded in the Charter is the best option for policy reform and that grassroots organizations working in coalitions continue to make meaningful social change as the policy battle continues. How it fits theme: The political power of the Canadian government has important implications for all citizens, but that power is not exerted equally against all sectors of society. There is implicit power in policy and practice that has lived consequences for those living in communities that experience systemic inequalities in healthcare, employment, and environment. However, these systemic barriers do not render individuals powerless. Grassroots movements are the fundamental origin of all civil rights victories experienced thus far, and will continue to have an integral role in changing the balance of power for generations to come. The example of environmental racism in Canada is a good place to examine the role of state power in racialized communities. At the same time, the individuals fighting against environmental racism through policy and social movements simultaneously are an inspiring example of resistance in praxis.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.128 | 0.040 |
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".