Blockades or Breakthroughs?
Bibliographic record
Abstract
Blockades have become a common response to Canada's failure to address and resolve the legitimate claims of First Nations. Blockades or Breakthroughs? debates the importance and effectiveness of blockades and occupations as political and diplomatic tools for Aboriginal people. The adoption of direct action tactics like blockades and occupations is predicated on the idea that something drastic is needed for Aboriginal groups to break an unfavourable status quo, overcome structural barriers, and achieve their goals. But are blockades actually "breakthroughs"? What are the objectives of Aboriginal people and communities who adopt this approach? How can the success of these methods be measured? This collection offers an in-depth survey of occupations, blockades, and their legacies, from 1968 to the present. Individual case studies situate specific blockades and conflicts in historical context, examine each group’s reasons for occupation, and analyze the media labels and frames applied to both Aboriginal and state responses. Direct action tactics remain a powerful political tool for First Nations in Canada. The authors of Blockades or Breakthroughs? Argue that blockades and occupations are instrumental, symbolic, and complex events that demand equally multifaceted responses. Contributors include Yale D. Belanger, Tom Flanagan, Sarah King, P. Whitney Lackenbauer, David Rossiter, John Sandlos, Nick Shrubsole, and Timothy Winegard.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.025 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".