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Record W4255362440 · doi:10.32920/ryerson.14656305.v1

Promoting CanCon in the age of new media

2021· preprint· en· W4255362440 on OpenAlexaffabout
Chris Mejaski

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsGovernment (linguistics)Context (archaeology)Public relationsValue (mathematics)Digital mediaPolitical scienceConsumption (sociology)BusinessSociologySocial scienceGeographyLawComputer science

Abstract

fetched live from OpenAlex

Canadian broadcasting policy has long pursued the belief that content produced by and for Canadians holds cultural value for its domestic audiences, in addition to economic significance for Canada's media industries. As the capabilities of wireless and mobile technologies have developed to allow consumption of content traditionally broadcast on television, stakeholders have questioned how to ensure culturally-rich, domestically-produced content is available for Canadian audiences by such means. As industry stakeholders have debated the potential value of Canadian content in an increasingly globalized media landscape, technologies have continued to advance, and Canadians have increasingly turned to new media to be informed and entertained. With a lengthy history of media regulation, this paper will demonstrate how the Canadian government's slow, uncoordinated response to developing new media policy effectively perpetuates inhibiting tensions between cultural and economic goals. Questions that frame this enquiry include: What role does Canadian content play as a reflection of Canadian culture and support of the production industry within Canada's traditional broadcasting system? Is regulation of new media important to maintain traditional policy goals? If so, what kinds of regulation might be implemented in this new context? And to what degree does current new media policy succeed in pursuing cultural and industrial goals historically common to Canadian media regulation? In pursuing these questions, this paper will draw conclusions regarding the benefits of federal new media policy, and how the government can better advance domestic digital media production, as technologies continue to evolve.

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)0.005
metaresearch head score (Gemma)0.014
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 score0.180
Threshold uncertainty score0.444

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0150.025
Scholarly communication0.0170.008
Open science0.0010.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.125
GPT teacher head0.326
Teacher spread0.200 · 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 routes2
Has abstractyes

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