Join Christians, Jews in tackling hatred
Bibliographic record
Abstract
I refer to Dr Kaleem Alam's "Muslims should take legal path", where he refers to Canadian Prime Minister Justin Trudeau's statement on the Charlie Hebdo republication of the Prophet Muhammad (PBUH) drawings on Sept 2 that indeed stands in contrast to French President, Emmanuel Macron. The latter's defence of France's so-called uncompromising liberalism - as exemplified by Charlie Hebdo's republication of derogatory drawings of the Prophet - as a lifeblood of its democracy stirred controversy even within the country and beyond the Muslim world. Let the French President be reminded that it was countryman Jean-François Flauss, a Professor at the University of Paris II (Pantheon-Assas), who wrote in 2009 - years before Macron was elected president in 2017 - that European jurisprudence very clearly condemns any form of hate speech in principle. [See Flauss, Jean-François (2009) "The European Court of Human Rights and the Freedom of Expression," Indiana Law Journal: Vol. 84 : Iss. 3 , Article 3. Available at: https://www.repository.law.indiana.edu/ilj/vol84/iss3/3]
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.018 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.030 | 0.010 |
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".