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Record W3121420360 · doi:10.5325/jinfopoli.4.2014.0001

A Tale of Two Regulators: Telecom Policy Participation in Canada

2014· article· en· W3121420360 on OpenAlexfundaboutno aff
Tamara Shepherd, Gregory Taylor, Catherine A. Middleton

Bibliographic record

VenueJournal of Information Policy · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsnot available
FundersIndustry CanadaAustralian Government
KeywordsGovernment (linguistics)Public interestPublic policyCommissionPublic relationsWork (physics)Circumstantial evidencePublic administrationPolitical scienceSociologyLawEngineering

Abstract

fetched live from OpenAlex

Abstract What are the challenges to effective academic participation in telecommunications policymaking? In this article, the authors analyze their experiences with the Canadian Radio-television and Telecommunications Commission and Industry Canada as examples. Their goal is to increase academic policy engagement despite negligible government support for public interest advocacy, as traditional public interest values are discarded by regulators because new technologies are framed as individual rather than collective. Industry Canada is deemed opaque with an “advocacy deficit,” though the CRTC is more transparent and inviting. To succeed in both venues, academics need to work with advocacy organizations as “circumstantial activists.” Such academic participation can offer new conceptual frameworks, add nuance to discourse, substantiate the use of scholarly research in policy debates, and add to policy theory building.

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)0.021
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.212
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0800.034
Scholarly communication0.0270.006
Open science0.0030.012
Research integrity0.0120.016
Insufficient payload (model declined to judge)0.0070.000

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 head0.010
GPT teacher head0.326
Teacher spread0.316 · 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 designObservational
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

Citations26
Published2014
Admission routes2
Has abstractyes

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