MétaCan
Menu
Back to cohort
Record W4389965030 · doi:10.16995/pr.9171

‘Information, Please’: Brian O’Nolan and the Radio

2023· article· en· W4389965030 on OpenAlexaff
Joseph LaBine

Bibliographic record

VenueThe Parish Review Journal of Flann O Brien Studies · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsIrishContext (archaeology)ScholarshipRadio programAmateurAudience measurementMedia studiesHistoryArtLiteratureArt historySociologyPhilosophyPolitical scienceLaw

Abstract

fetched live from OpenAlex

This article proposes Irish radio broadcasting as an unexplored context for new directions in Flann O’Brien studies. Brian O’Nolan’s involvement in Irish radio spans at least two decades, from the early 1930s into the 1950s, yet the contributions of O’Nolan and his literary circle to Radio Éireann and the BBC remain an under-researched area of Flann O’Brien scholarship. Scholars are faced with the absence of a sound archive to refer to; but this article argues that such absences are part of the ephemeral nature of radio as a medium, and that we must view O’Nolan’s work in radio as an emerging, amateur practice within a wider, sustained artistic project. Though we cannot resurrect the live performances themselves, the article draws on new archival evidence to offer a short history of O’Nolan’s radio appearances. It attempts to fill the gaps produced by lost media with original radio schedules, reviews, letters, and typescript drafts, and by contextualising O’Nolan’s portrayals of radio within a wider social and technological milieu, via the radio-related activity of his circle (Niall Sheridan, Donagh MacDonagh, Niall Montgomery). This context helps us to see how radio aesthetics influenced O’Nolan’s metafictional writing, as demonstrated through close readings of how the modernist ‘radio’ mode informed ‘!CEÓL!’ (1932), Blather (1934), and At Swim-Two-Birds (1939).

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.086
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.054
GPT teacher head0.280
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe Parish Review Journal of Flann O Brien StudiesSame topicCinema and Media StudiesFrench-language works237,207