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Record W4406018944 · doi:10.5931/djim.v18i1.12314

The right to read in a censored world: The position of young people, educators, and librarians in protecting intellectual freedom

2024· article· en· W4406018944 on OpenAlexaffvenue
Emma Hak-Kovacs

Bibliographic record

VenueDalhousie Journal of Interdisciplinary Management · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPosition (finance)Intellectual freedomPolitical scienceFreedom of informationSociologyPublic relationsPsychologyLawBusinessCensorship

Abstract

fetched live from OpenAlex

The purpose of this paper is to examine the topics of intellectual freedom and censorship, particularly in the context of restricting access to ‘controversial’ books in libraries and classrooms. Although censor­ship exists in various forms, it always results in the suppression of information access and dispro­po­rtionately targets works by LGBTQIA+ authors and authors of colour. This paper brings into focus the experiences of young people (who are often the most affected by censorship due to their care­giv­ers/authority figures deeming material unsuitable), highlighting the importance of fostering their inde­pendence as readers and decision makers. Additionally, it explores the vital role of educators and librari­ans in protecting intellectual freedom, discussing possible constructive responses to censorship that fos­ter inclusivity and access to information.Keywords: censorship, reading, intellectual freedom, education

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)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0180.029
Scholarly communication0.0150.009
Open science0.0010.010
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.299
Teacher spread0.289 · 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.

Study designQualitative
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

Citations0
Published2024
Admission routes2
Has abstractyes

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