Crisis, What Crisis? Immigrants, Refugees, and Invisible Struggles
Bibliographic record
Abstract
Different evocations of “crisis” create distinct categories that in turn evoke certain social reactions. After 2008 Greece became the epicentre of the “financial crisis”; since 2015 with the advent of the “refugee crisis,” it became the “hotspot of Europe.” What are the different vocabularies of crisis? Moreover, how have both representations of crisis facilitated humanitarian crises to become phenomena for European and transnational institutional management? What are the hegemonically constructed subjects of the different crises? The everyday reality in the crisis-ridden hotspot of Europe is invisible in these representations. It is precisely the daily, soft, lived, and unspoken realities of intersecting crises that hegemonic discourses of successive, overlapping, or “nesting crises” render invisible. By shifting the focus from who belongs to which state-devised category to an open-ended, polyvocal account of capitalist oppressions, we aim to question the state’s and supranational efforts to divide the “migrant mob” into discrete juridical categories of citi-zens (emigrants), refugees, and illegal immigrants, thereby undermining coalitional struggles between precaritised groups.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".