Everyday Cruelties: Political Economies of Migration and Indifference
Bibliographic record
Abstract
Abstract This article examines how attitudes and structures of indifference to oppression and global inequality—practices of cruelty—are cultivated at both macro (institutional) and micro (everyday life) levels. First, following (Inayatullah and Blaney 2010a, 2010b), I suggest that a core premise of classical political economy—the split between self and other—is depoliticized and rationalized by contemporary discourses of international political economy. This depoliticization is a condition of possibility for attitudes of indifference. Consequently, understanding attitudes and structures of indifference requires re-politicizing political economy as a cultural encounter structured through gendered and racialized hierarchies. Second, I argue that indifference to cruelty is cultivated through recourse to ethical rather than political imperatives, which foreground ethical action in ways that continue to depoliticize the cruelties of global inequality. Two sites animate this project and foreground a form of banal cruelty justified through the cultivation of political indifference: at the microlevel, a dystopian short story that takes an ethicized indifference as the basis for accounting for racialized and gendered labor migration (George Saunders’ “The Semplica Girl Diaries”), and, at the macro-level, Canada's Temporary Foreign Worker programs, which produce depoliticized justifications for systemic racialized exploitation. I argue that this ethicization of political relationships is a way of precluding engagement with the colonial politics of indifference and the everyday cruelties of political economy through which inequalities and exploitations are produced and reproduced.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.032 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".