Prohibition of religious slaughter in Executief van de Moslims van België and others v. Belgium : process-based review and a new legitimate aim
Bibliographic record
Abstract
In Executief van de Moslims van België and others v Belgium the European Court of Human Rights (the ECtHR, the Court) assessed the compatibility of decrees adopted in Flanders and Wallonia banning the slaughter of animals without prior stunning, as practiced by observant Muslims and Jews who eat Halal or Kosher meat. While these bans exceptionally allow such stunning to be reversible/non-lethal in the context of religious slaughter, the applicants alleged that they were discriminatory and incompatible with the right to freedom of religion. Echoing the previous findings of the European Court of Justice (CJEU), the ECtHR found that this was not the case. The complex and sensitive nature of this case can hardly be overstated, particularly in light of the CJEU’s previous consideration and acceptance of the ban and the value which should rightly be accorded to the protection of animal welfare. However, this judgment raises serious questions about the Court’s attitude to the right to freedom of religion under Article 9 and its approach to evaluating general restrictions thereof. In this blogpost, we focus on three issues in particular: the limited/non-existent protection of minority rights resulting from the Court’s application of process-based review; the flexible introduction of (new) legitimate aims and the heavy weight accorded thereto; and the comparability of the applicants with groups for which an exception was made.
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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 | 0.071 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.020 | 0.009 |
| 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 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".