The Hero, the White Savior, and the Smuggler: Criminalized Figures in the Landscape of Solidarity Toward Migrants
Bibliographic record
Abstract
One recent shift in the ever-expanding crackdown on migration and implementation of a hostile environment for migrants in the EU has been the criminalization of migrant solidarity. Using various legal tools, EU governments have been trying to hinder solidarity actions from civil society. In particular, a narrative depicting civilians helping migrants as criminals has been elaborated by European organizations and strengthened by far-right groups and dominant press outlets. In reaction, a counter-narrative has been constructed and spread by pro-migrant groups and liberal media, which presents criminalized activists as criminalized heroes and their actions as humanitarian. Based on a critical discourse analysis of academic texts, press articles, and empirical research with pro-migrant activists, this article examines two criminal figures from the civilian search and rescue field: the “activist associated with smugglers” and its counterpart, the “criminalized hero.” Through the lens of figuration of crime and social justice, the article brings a new understanding of the de- and repoliticization processes that occur in the field of humanitarian help and migration. By analyzing these two figures, the paper also contributes to a better understanding of the competing moral orders underpinning criminal and social justice claims in the field of solidarity toward migrants. On the one hand, the figure of the activist associated with smuggler is part of a criminal justice narrative depicting migration as a threat to political, social, and economic stability. On the other hand, the criminalized hero figure includes a counter-narrative to this moral order based on the defense of a social justice frame of solidarity and the protection of human rights. Within the pro-migrant activist’s scene, the criminalized hero and its social justice frame are criticized for reproducing racist and post-colonial practices of humanitarianism.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.032 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".