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Record W2011943997 · doi:10.1080/1461670042000246070

Increasing circulation? a comparative news‐flow study of the Montreal<i>Gazette</i>'s hard‐copy and on‐line editions

2004· article· en· W2011943997 on OpenAlexafffundabout
Mike Gasher, Sandra Gabriele

Bibliographic record

VenueJournalism Studies · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsConcordia University
FundersConcordia University
KeywordsNewspaperPublishingCirculation (fluid dynamics)The InternetPolitical scienceNews mediaAdvertisingNews valuesMedia studiesSociologyBusinessLawComputer scienceWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

International news‐flow research has repeatedly identified significant imbalances in the global exchange of news among regions of the world. With the emergence of thousands of news sites on the World Wide Web, and the corresponding ability of news audiences to access these sites, the Internet offers the technological capacity to globalize media content. This paper seeks to test that possibility by exploring the way one Canadian daily newspaper, the Montreal Gazette, occupies the geography of the Internet with its on‐line news operation. The paper reports on an exploratory comparative news‐flow study of the Gazette's hard‐copy and on‐line editions to determine whether on‐line publishing has prompted the Gazette to alter the boundaries of its news coverage. While the paper concludes that, indeed, the Gazette's website consistently carried far more international news items than its hard‐copy edition, it also notes that this distinction is largely explained by the website's very heavy reliance on wire‐service copy and its emphasis on sports news.

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)0.013
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: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.552

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.009
Science and technology studies0.0040.003
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.117
GPT teacher head0.387
Teacher spread0.270 · 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

Citations27
Published2004
Admission routes3
Has abstractyes

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