Toronto’s Anti-Racist Action, 1992-2003: “Expose, Oppose and Confront”
Bibliographic record
Abstract
The study sheds light on the effectiveness of direct action in campaigns against the far right, by examining the Toronto activist group Anti-Racist Action (ARA-TO) between 1992 and 2003. ARA-TO’s mission was to “expose, oppose and confront” far-right opponents. Over two peak periods of activity, the group contributed to the collapse of the far-right Heritage Front and limited the growth of other far-right organizations, while fostering anti-racist youth culture and supporting a continent-wide network of youth-based anti-racist groups. The study draws upon personal recollections of the author (a past participant), 25 unstructured open-ended interviews, artifacts from the period, and print media coverage to create a thick, multi-perspectival description of ARA-TO and its relationships with other anti-racist organizations. It offers insight into the radical flank effect within a movement/counter-movement dynamic and reveals how, under certain conditions, radical organizations can remake the political field.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".