Words don’t come easy: Al Jazeera’s migrant–refugee distinction and the European culture of (mis)trust
Bibliographic record
Abstract
Al Jazeera’s August 2015 editorial decision to substitute ‘refugee’ for ‘economic migrant’ in its coverage of ‘the Mediterranean Migration Crisis’ provides an opportunity to re-frame the relationship between the politics of race, immigration and media representations of refugees. Situating the broadcaster’s publicly announced rationale for the decision within a critique of the migrant–refugee dichotomy enforced by European public policy, this article, first, demonstrates that the policy couplet mobilizes oppositional yet interdependent identities. The discursive distancing of ‘migrant’ from ‘refugee’ in news content does not dislodge their mutually reinforcing power to define the parameters of ‘inclusion’. Second, the article examines how the policy onus placed on refugees to justify their claim as ‘victims’ reproduces racialized codes of belonging that perpetuate the denial of autonomy. Persons seeking refuge in Europe must sustain an identity of ‘non-threatening victim’ if they are to gain recognition in a securitized culture of (mis)trust. Al Jazeera’s intervention strengthens the media representation of refugees as human beings without choice; yet, the broadcaster’s decision to ‘give voice’ by ‘challenging racism’ does not break the European political consensus on immigration and asylum that positions ‘non-Western’ peoples as victim/pariah, to be ‘saved’ and ‘suspected’. The media–policy–migration nexus ensures that refugee exclusion is always possible.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".