Dismantling White Privilege: The Black Lives Matter Movement and Environmental Justice in Canada
Bibliographic record
Abstract
On August 12, 2017, in Charlottesville, Virginia, alt-right/White supremacy groups and Black Lives Matter (BLM) supporters came face-to-face regarding what to do about public monuments that celebrate key figures from slavery and the Jim Crow era. White supremacists and White nationalists did not hide their racist ideologies as they demanded that their privileged place in history not be erased. The BLM movement, which challenges state-sanctioned anti-Black racism, was ready to confront themes of White discontent and reverse racism, critiques of political correctness, and the assumption that racialized people should know their place and be content to be the subordinate other.It is easy to frame the events in Charlottesville as indicative of US-specific race problems. However, a sense that White spaces should prevail and an ongoing history of anti-Black racism are not unique to the United States. The rise of Canadian activism under the BLM banner also signals a movement to change Canadian forms of institutional racism in policing, education, and the labor market. This article responds to perceptions that the BLM movement has given insufficient attention to environmental concerns (Pellow 2016; Halpern 2017). Drawing on critical race theory as a conceptual tool, this article focuses on the Canadian context as part of the author’s argument in favor of greater collaboration between BLM and the environmental justice (EJ) movement in Canada. This article also engages with the common stereotype that Blacks in Canada have it better than Blacks in the United States.
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 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 | 0.000 | 0.001 |
| 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".