MétaCan
Menu
Back to cohort
Record W1996706811 · doi:10.7202/1013032ar

“Dignitizing” Free Speech in Israel: The Impact of the Constitutional Revolution on Free Speech Protection

2012· article· en· W1996706811 on OpenAlexvenueaboutno aff
Guy E. Carmi

Bibliographic record

VenueMcGill Law Journal · 2012
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsDignitySupreme courtFree speechLawPolitical scienceBill of rightsHuman rights

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.027
Scholarly communication0.0080.006
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.027
GPT teacher head0.257
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueMcGill Law JournalSame topicHate Speech and Cyberbullying DetectionFrench-language works237,207