MétaCan
Menu
Back to cohort
Record W2085385322 · doi:10.5964/ejop.v9i2.574

On the Freedom of Speech and Expression: Interview with Noam Chomsky

2013· article· en· W2085385322 on OpenAlexaboutno aff
Beatrice Popescu, Noam Chomsky

Bibliographic record

VenueEurope’s Journal of Psychology · 2013
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsChomsky hierarchyExpression (computer science)PsychologyComputer sciencePhilosophyProgramming languageRule-based machine translation

Abstract

fetched live from OpenAlex

On the Freedom of Speech and Expression: Interview with Noam Chomsky Authors Beatrice Popescu EJOP Founding Editor, University of Bucharest, Bucharest, Romania Noam Chomsky Abstract No abstract available. PDF HTML Article info Impact Citations How to Cite License Published at 31. May 2013 https://doi.org/10.5964/ejop.v9i2.574 Issue: Vol. 9 No. 2 (2013) Section: Interview Share: Z Popescu, B., & Chomsky, N. (2013). On the Freedom of Speech and Expression: Interview with Noam Chomsky. Europe’s Journal of Psychology, 9(2), 214-219. https://doi.org/10.5964/ejop.v9i2.574 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX This work is licensed under a Creative Commons Attribution (CC BY) 3.0 International License. PlumX Dimensions Views: Total Abstract PDF HTML 2902 411 256 2235 Downloads: Download data is not yet available.

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)0.013
metaresearch head score (Gemma)0.029
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: none
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0180.017
Scholarly communication0.0060.014
Open science0.0020.007
Research integrity0.0060.025
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.255
Teacher spread0.234 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueEurope’s Journal of PsychologySame topicHate Speech and Cyberbullying DetectionFrench-language works237,207