Bibliographic record
Abstract
This article introduces the symposium on Glen Coulthard’sRed Skin, White Masks. It begins by situating the book’s publication in the wake of the extensive mobilisations of the Idle No More movement in Canada in 2012–13. Coulthard’s strategic hypotheses on the horizons of Indigenous liberation in the book are intimately linked to his participation in these recent struggles. The article then locatesRed Skin, White Maskswithin a wider renaissance of Indigenous Studies in the North American context in recent years, highlighting Coulthard’s unique and sympathetic extension of Marx’s critique of capitalism, particularly through his use of the concept of ‘primitive accumulation’. Next, the article outlines the long arc of the argument inRed Skin, White Masksand the organisation of the book’s constituent parts, providing a backdrop to the critical engagements that follow from Peter Kulchyski, Geoff Mann, George Ciccariello-Maher, and Roxanne Dunbar-Oritz. The article closes with reflections on Coulthard’s engagement with Fanon, who, besides Marx, is the most important polestar inRed Skin, White Masks.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.005 |
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".