Bibliographic record
Abstract
It is difficult to define blasphemy. What is regarded as blasphemous will depend on the values prevalent in a given society. In general, it includes denigrating and insulting expressions targeted toward God and other aspects of religion. My thesis is that blasphemy, to the extent it should be dealt with by the law, should be regarded a sub-category of hate speech. The law should concern itself only with those aspects of blasphemy which incite hatred against a group which is identifiable on the basis of religion. More specifically, I argue that Pakistan should repeal its blasphemy law (s. 295-c Penal Code, 1860) because blasphemous prosecutions are politically, socially, economically and culturally motivated while religion is only used as a legitimizing tool by opportunists. Canada is an example in this regard. While the Canadian Criminal Code prohibition of blasphemous libel (s. 296) is vague and would likely be held to infringe freedom of expression unjustifiably, the hate speech provisions of the Criminal Code are much more precisely worded and have been upheld by the Supreme Court of Canada as a justifiable infringement of freedom of expression. Thus, the argument of this thesis is that the approach taken in s. 319(2) offers a useful model for modernizing Pakistan's laws on blasphemy as hate speech.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| 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".