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Record W17515347 · doi:10.3138/topia.25.51

The Aesthetics of Transcultural Revolution: Freedom Songs in Halifax and Toronto, 1965 to 1967

2011· article· en· W17515347 on OpenAlexvenueaboutno aff
Krys Verrall

Bibliographic record

VenueTOPIA Canadian Journal of Cultural Studies · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsSolidarityInjusticePolitical scienceSociologyLawSingingSpanish Civil WarPrivilege (computing)Media studiesHistoryPolitics

Abstract

fetched live from OpenAlex

The story of the 1960s civil rights movement is conventionally viewed as a distinctly American phenomenon arising from that nation’s longer history of slavery, civil war, segregation, and racial violence. The following paper challenges this convention by looking at the dynamic relationship between black activists in Halifax and Toronto and the Student Non-violent Coordinating Committee (SNCC), a radical organization based in southern states from 1965 to 1967. Indeed, neither SNCC nor Canadian activists saw themselves in local or even national terms. While their aim was to transform local injustice, their sightlines were transnational. In this, singing proved instrumental. This paper takes two instances from 1965—the Selma, Alabama, solidarity protests in Toronto and the Freedom Singers Maritime Tour—to chart how activists on both sides of the border recognized music’s strategic importance to public protest. Both events mark a high point in SNCC/Canadian solidarity. However, the productive intersection of north-south activism with singing was fleeting. By 1966 SNCC’s internal transformations had adverse repercussions on its Canadian support base. At the same time, singing’s place as the dominant realization of culture with revolutionary praxis also changed in ways that would privilege the visual over the aural.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.262
Teacher spread0.224 · 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 teacher head, 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

Citations4
Published2011
Admission routes2
Has abstractyes

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