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Record W4317801817 · doi:10.3138/cjc.2022-0053

Canadian Trash, American Treasure: YTV, Nickelodeon, and the Production of Canadian Children’s Television Distribution

2023· article· en· W4317801817 on OpenAlexaffvenueabout
Patrick Bonner

Bibliographic record

VenueCanadian Journal of Communication · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsConcordia University
Fundersnot available
KeywordsEntertainmentAdvertisingProduction (economics)TreasureRelation (database)Distribution (mathematics)Media studiesPolitical scienceSociologyBusinessGeographyEconomicsLaw

Abstract

fetched live from OpenAlex

Background: YTV was one of Canada’s most popular television networks during the 1990s. Despite its many contributions to a vibrant and influential children’s television industry during that period, research on the network is scarce. Analysis: This article analyzes the relationship between YTV, Canada’s first dedicated children’s network, and Nickelodeon, the popular U.S. children’s brand. It also examines how YTV was discursively and practically organized in relation to Nickelodeon in its nascent years. As well, it considers how YTV built on Nickelodeon’s production of its audience as “consumer citizens.” Conclusions and implications: This once dynamic relationship has come to favour the U.S. industries through the Canadian entertainment conglomerate Corus Entertainment’s transnational-vertical business operations.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.493

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.004
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.000

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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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