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Record W2911291748 · doi:10.1177/1527476418824299

Television for the Peace Arch Country: Transnational Broadcasting History in the Pacific Northwest

2019· article· en· W2911291748 on OpenAlexaboutno aff
Helen Morgan Parmett

Bibliographic record

VenueTelevision & New Media · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
FundersUniversity of Vermont
KeywordsPublic broadcastingConstitutionCitizenshipDemocracyMedia studiesCommunismBridge (graph theory)Political scienceCapitalismBroadcasting (networking)ArchSociologyLawGeographyPoliticsArchaeology

Abstract

fetched live from OpenAlex

This article contributes to international broadcasting history through a case study of a local, independent television station in the Pacific Northwest. KVOS-TV was one of a few stations on the U.S./Canadian border that sought out a cross-border audience, but it is unique in its efforts to produce programming to bridge these audiences into a unified viewing public that it termed the Peace Arch Country . The station’s international programming constituted its viewing public as translocal citizens in ways that supported the broader global ambitions of the Pacific Northwest region, as well as responded to and promoted the global ambitions of western liberal democracy and capitalism in the fight against Communism. KVOS-TV’s constitution of Peace Arch citizenship shows how television was a tool for creating translocal citizens, educating and governing them from a distance.

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)0.002
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 score0.587
Threshold uncertainty score0.822

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0240.011
Scholarly communication0.0080.006
Open science0.0010.004
Research integrity0.0010.005
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 head0.051
GPT teacher head0.301
Teacher spread0.250 · 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
Published2019
Admission routes1
Has abstractyes

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