“Middle East conflict in Berlin schools”: on the affectability of “fake news”
Bibliographic record
Abstract
Abstract The article revisits my older work on moral panics over “Muslim homophobia” and youth crime to make sense of the arrival of a new criminalized figure: the Palestinian school kid who becomes prone to terrorism and antisemitism after consuming “fake news” on social and Arabic-language media. It addresses the current outbreak of anti-Palestinian racism in Germany as the latest expansion of an archive of criminalization that targets young people who, far from innocent and deserving of care and education, are constructed as folk devils that require heavy-handed punishment, segregation and deportation. While former panics have singled out the problematic heterosexualities of Muslim populations that fail to catch up with women-and-LGBT-friendly communities that care about diversity, the debate about the “Middle East conflict in Berlin schools” foregrounds media use as a central determinant of cultural pathology. This departure from languages of care and diversity, the article argues, reflects a dehumanizing tendency in racial capitalism that appears increasingly undisguised.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.010 | 0.016 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".