Race and Populist Radical Right Discourses: Implications for Roma Education Policy in Hungary
Bibliographic record
Abstract
Non-government organizations and policy makers agree that the best route to eradicating the widespread discrimination and poverty among the Roma is to improve the quality of and access to education. A cursory glance at the Hungarian Government website suggests that policy makers are on top of the problem with good laws and initiatives in place. Yet, indicators from non-government groups and academics suggest the situation remains bleak for the Roma, and practices such as the segregation of Roma school children persist. Progressive change in Hungary first requires a serious confrontation of the widespread and deeply ingrained racism against the Roma. This paper makes no attempt at such an ambition; however, the paper aims to begin acknowledging the role race plays in populist radical right discourses about education policies in Hungary using a discourse analysis method informed by Critical Race Theory. The paper advances two arguments. First, there is a mismatch between official policy and actual progress on Roma education. Second, an examination of how populist radical right discourses about the Roma are racialized provides insight into why there is a mismatch.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".