Bibliographic record
Abstract
What do apologies apologize for? More precisely, what do the apologies regularly pronounced by states for some atrocity or other actually accomplish? This question animates my article. State apologies became an integral element of global political culture in the early 21st century. These politics of regret are reshaping Canadian national culture, most pronouncedly with the apologies for the Indian Residential School System ( CBC News 2008a ; McIntyre 2017 ) and the Komagata Maru ( CBC News 2008b ; Trudeau 2016 ). While Public Inquiries and Royal Commissions have long served as state responses to political mobilization, deployment of the machinery of regret has fast become the predictable response to accusations of atrocities, including genocide, enslavement and racial violence. Drawing on Frantz Fanon’s and Walter Benjamin’s ideas on violence, colonial in the case of Fanon (1961) , law in that of Benjamin (1996) , I examine the apologies delivered to Indigenous peoples and South-Asian diasporic communities by the Canadian state. Locating these pronouncements in the histories of violence they index, I demonstrate how such apologies function as techniques of violence that advance settler power structures and narratives of nationhood. My argument here is that apologies are themselves acts of violence which rework histories of brutalization to meet the political destabilizations of the present. Apologies thus reorganize the racial violence of settler societies, drawing sections of subjugated populations into waging this violence and, in the process, derail resurgent politics of decolonization, abolitionism and anti-racism.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".