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Record W4285246053 · doi:10.5040/9781350191747.ch-013

The Transcription Centre and the Coproduction of African Literary Culture in the 1960s

2022· other· en· W4285246053 on OpenAlexaboutno aff
ASHA ROGERS

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoproductionTranscription (linguistics)SociologySocial scienceLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Sub-Saharan African literary producers working in the 1960s faced a bipolar landscape characterized by the intersecting pressures of the Cold War and decolonization against which they built networks, cultivated audiences, and created new outlets for their work in ways not always immediately reducible to ideological determinants. This chapter revisits one space in which creative work was being produced at the time: the London-based Transcription Feature Service, or Transcription Centre (1962–77). Established in early 1962, the Centre recorded English-language radio programs on topics related to African literature, art, and culture for sale, distribution, and broadcast in newly independent African countries, and elsewhere in the world. Founded and directed by Dennis Duerden, a former BBC employee, and produced by the South African, and London-based writer, critic, and journalist Lewis Nkosi, the Transcription Centre created one-off features and series, and regular shows like the weekly magazine program Africa Abroad (1962–6), which combined interviews with African or West Indian artists or writers passing through London with a lively mix of review pieces and performances. Within a few short years the Centre had produced over five hundred radio programs, recordings of which found their way beyond English-speaking African stations to the Caribbean and North America, with radio networks extending to India, France, Canada, and Australia. One of the lesser-known cultural hubs of the period, the Transcription Centre adds several important strands to discussions of Cold War literary culture. It illustrates the issues of mobility, diaspora …

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)0.009
metaresearch head score (Gemma)0.017
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 score0.037
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.006
Science and technology studies0.0180.025
Scholarly communication0.0160.008
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.002

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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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
Published2022
Admission routes1
Has abstractyes

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