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Record W2031499177 · doi:10.1177/0038038513500097

The Greatest Subversive Plot in History? The American Radical Right and Anti-UNESCO Campaigning

2013· article· en· W2031499177 on OpenAlexaff
Randle J. Hart

Bibliographic record

VenueSociology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsSaint Mary's University
FundersUniversität Heidelberg
KeywordsCensorshipContext (archaeology)Race (biology)SociologyPoliticsPolitical sciencePlot (graphics)Media studiesStatement (logic)Competition (biology)LawGender studiesHistory

Abstract

fetched live from OpenAlex

Through analysis of two social issues that held the potential for anti-UNESCO campaigning by the American Radical Right in the 1950s – UNESCO’s much publicized Statements on Race and the use of UNESCO textbooks in public schools and libraries – I argue that micromobilization contexts can create conditions of path dependency whereby the initiation of one campaign hinders other campaigns from developing. Specific micromobilization factors – past campaigning on similar issues, tactical expectations, an available pool of skilled activists, frame resonance, a national conservative media, and amenable polities – created favorable initial conditions for anti-UNESCO censorship campaigning, while competition from activists in another social movement restricted campaign development in response to UNESCO’s Statement on Race. The micromobilization context from which the censorship campaign emerged created conditions of path dependency which limited further the viability of American Radical Rightists developing a campaign in reaction to UNESCO’s Statement on Race.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.017
Scholarly communication0.0060.005
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.258
Teacher spread0.246 · 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 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

Citations17
Published2013
Admission routes1
Has abstractyes

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