Bibliographic record
Abstract
Enns reflects on the meaning of guilt and responsibility in the context of Indigenous struggles in Canada. While rarely uncomplicated, the question of who is to blame poses a unique challenge in the case of historical atrocities with enduring legacies. When those guilty of the original violations are long dead, yet leave behind institutions that perpetuate the conditions for oppression and privilege, it is tempting to assign collective guilt. With the help of Hannah Arendt and Karl Jaspers, who argued in the aftermath of World War II for a robust understanding of collective responsibility, distinct from individual guilt, Enns navigates the effects of oversimplifying these concepts. Central to her discussion is the dramatic shift in contemporary scholarly and public discourses on victimhood and identity – on victimhood as identity – since Arendt famously wrote: “Where all are guilty, no one is.” With reference to the parallel ways in which victimhood is assumed as a permanent state and granted moral authority in North American Indigenous and anti-Black racism struggles, Enns notes the limits of an identity-based politics, and argues for a richer understanding of collective responsibility – one that will create a future world with a better inheritance.
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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 | 0.002 | 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 | 0.014 | 0.052 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".