‘Perfect Vision’: An Examination of the Role of Census and Profiling Practices in Visualizing and Crafting Refugee ‘Groups’ under Contemporary Group-resettlement Programmes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article demonstrates how the characteristically visual practices of boundary-making around prospective refugee groups comprise an important and instrumentalized version of what Rogers Brubaker (2004) calls ‘groupism’—the assumption that ‘discrete, sharply differentiated, internally homogeneous and externally bounded groups’ are the ‘basic constituents of social life’ (2004: 8). Unlike individual resettlement, group-resettlement schemes (known as ‘Group Processing’ in Canada, ‘Priority-2 group referrals’ in the United States and the ‘Group Methodology’ at the United Nations High Commissioner for Refugees (UNHCR)) involve the resettlement of entire refugee groups. Preoccupations with security and the possibility of identity fraud in these programmes have led to a preference for what are perceived as easily identifiable, finite and homogenous refugee groups. Census and profiling practices permit authorities to visualize and draw boundaries around these types of groups. These practices are the preconditions for the writing of specific narratives of risk, persecution and flight in UNHCR group profiles. An examination of group resettlement reveals how officials do not just choose between pre-existing refugee groups based on racial, national and ethnic categories, but rather attempt to construct an idealized conception of groups reflected in Brubaker’s notion of groupism.
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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 | 0.004 | 0.001 |
| 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 it