“Dignitizing” Free Speech in Israel: The Impact of the Constitutional Revolution on Free Speech Protection
Bibliographic record
Abstract
This article examines the changes in the approach to the analysis of free speech rights in Israel. It demonstrates the growing shift from the American liberty-based influence in the 1980s to a more dignity-based, and principally Canadian- and German-inspired, model following the adoption of the partial bill of rights in the 1990s. This is demonstrated both by a statistical analysis of the Israeli Supreme Court free speech rulings in the past thirty years and by a substantive analysis of recent rulings in the areas of prior restraint, pornography, and libel. The statistical findings demonstrate that while human dignity rarely played a role in free speech rulings in the past, it plays a significant role today. Another indication of the “dignitization process” lies in the reference to foreign rulings. Moreover, a substantive examination of the Israeli Supreme Court’s free speech rulings from the last decade reveals the dignitization process both in rhetoric and outcomes. This article offers a means of strengthening the protection that free speech receives in Israel by divorcing the constitutional protection of free speech from the concept of human dignity, and by focusing on the value of liberty. This can be achieved by the incorporation of the unenumerated right to free speech via the liberty clause within Basic Law: Human Dignity and Liberty.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".