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Record W2890777954 · doi:10.4324/9781315191324

Challenges to Democracy

2018· book· en· W2890777954 on OpenAlexaboutno aff
Raphael Cohen‐Almagor

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicWar, Ethics, and Justification
Canadian institutionsnot available
Fundersnot available
KeywordsDemocracyPolitical scienceComputer scienceLawPolitics

Abstract

fetched live from OpenAlex

This title was first published in 2000: The essays gathered in this volume cover a wide range of theoretical and practical issues concerning a variety of problems which democracies confront time and again. Their aim is to look at challenges to democracy that evolve from within democracy. The discussion sets out to examine how democracies, in different times, dealt with attempts to undermine democratic processes and fundamental human rights. The design of the book is both interdisciplinary and comparative, offering historical, philosophical, legal, sociological, political and media perspectives of renowned scholars from the UK, Israel, the USA and Canada. They analyze how different societies try to cope with and find answers for attacks against them by political extremists, cultural chauvinists, terrorists, hate groups and other radical movements.

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)0.002
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0110.007
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0280.006

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 head0.172
GPT teacher head0.289
Teacher spread0.118 · 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
GenreOther

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

Citations0
Published2018
Admission routes1
Has abstractyes

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