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Record W3013594026 · doi:10.4324/9780429345777-3

The Global Local

2019· book-chapter· en· W3013594026 on OpenAlexaboutno aff
James Benedict Brown

Bibliographic record

VenueRIBA Publishing eBooks · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

The dispersed population of Canada creates many problems for traditional network television. As Global’s prime-time national news–Global National #8211; argets an early evening audience across the country, the programme must be pre-recorded and time-shifted in each market. The ‘operational efficiency’ to which the Global Television press release referred meant that local evening newscasts would no longer be produced in the city where they were broadcast. In much the same way as BBC Broadcasting House would soon demonstrate its journalistic authority to viewers through the careful creation of a mediated space of journalistic production, local newscast was employing well-worn codes of television production to demonstrate expertise. Chroma-key studios have been used in film and television for several decades. The most familiar demonstration of technology in television is weather map. Global Television demonstrates how it might be possible to employ four spatial codes in the delivery of its mandatory local news programming without recourse to building vast newsrooms and large studio spaces.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.173
Threshold uncertainty score0.344

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.003
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0900.019

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 head0.029
GPT teacher head0.266
Teacher spread0.238 · 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
Published2019
Admission routes1
Has abstractyes

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