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Record W2955618433 · doi:10.22230/cjc.2019v44n2a3117

The LTTV Consultations: Mapping Old and New Interests in Television Today

2019· article· en· W2955618433 on OpenAlexaffvenueabout
Mary Elizabeth Luka, Catherine A. Middleton

Bibliographic record

VenueCanadian Journal of Communication · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsCLARITYStakeholderInfographicAdvertisingConsistency (knowledge bases)Intersection (aeronautics)Public relationsProcess (computing)Distribution (mathematics)MarketingPolitical scienceSociologyComputer scienceBusinessEngineering

Abstract

fetched live from OpenAlex

This article unpacks two infographic analyses to highlight two important themes regarding changes to the distribution systems and business models for the converging broadcast and telecommunications industry. First is that the recent revolution in production practices is now reverberating through the distribution system, as illustrated by a provisional mapping of a complex stakeholder ecosystem. Second is the clarity and consistency of the messages received from Canadians during CRTC consultations. In the Let’s Talk TV consultations, consumer-citizen messages centered on the desirability of readily available online and on-demand content, particularly Canadian and local content. By showing various stakeholders and their points of intersection throughout the process, this article aims to make a complex business more comprehensible, or at least more accessible, to a broad audience.

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)0.002
metaresearch head score (Gemma)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.821

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0100.006
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.043
GPT teacher head0.306
Teacher spread0.264 · 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

Citations1
Published2019
Admission routes3
Has abstractyes

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