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Record W4233570078 · doi:10.32920/15135900

Mediaucracy: Why Canada hasn't made global TV hits and how it can

2021· preprint· en· W4233570078 on OpenAlexaboutno aff
Irene Berkowitz

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsGlobalityLicensePolitical scienceKey (lock)HollywoodGlobalizationLawComputer scienceHistoryComputer securityArt history

Abstract

fetched live from OpenAlex

Why Canada hasn't made global hits and how it can is the story of the fiery collision between Canada's national TV policy and the global, online era. Featuring interviews with Hollywood showrunners, award-winning producers, and top policy leaders, it argues for a new goal -- globality -- policy that incentivizes global reach and popular content. Mediaucracy concludes with an original five-step, goal-driven, evidence-based, critical path including POM to COM, G-Score, and PM to AM. Called an "important, timely roadmap to a much-needed policy update," this 21st century tool kit will future-proof Canadian TV policy via the three key words in the TV biz: Audience, audience, audience. License:

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)0.003
metaresearch head score (Gemma)0.013
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: Empirical · Consensus signal: none
Teacher disagreement score0.102
Threshold uncertainty score0.738

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0240.014
Scholarly communication0.0210.008
Open science0.0020.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0230.002

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 head0.037
GPT teacher head0.295
Teacher spread0.258 · 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
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

Citations0
Published2021
Admission routes1
Has abstractyes

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