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Yellow Journalism

2008· other· en· W4247591107 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Encyclopedia of Communication · 2008
Typeother
Languageen
FieldArts and Humanities
TopicLiterature, Film, and Journalism Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSensationalismNewspaperJournalismPopulismPoliticsPolitical scienceEconomic historyMedia studiesTasteWorking classPejorativeSociologyLawHistory

Abstract

fetched live from OpenAlex

The term “yellow journalism” first emerged in the United States as a pejorative to characterize the news produced by publishers William Randolph Hearst and Joseph Pulitzer in their competition for New York City readers during the late 1890s. Their success in achieving daily circulations surpassing one million helped spread their innovations, including → sensationalism, to other newspapers. With Pulitzer and Hearst, the US news industry joined that of other industrialized democracies at the turn of the century, including Sweden, Germany, Canada, and England (with the Northcliffe revolution), in evolving from a limited “class” press to a “mass” medium. These mass newspapers adopted varying proportions of sensationalism, populism, and socialism to address the interests of new, urban, working‐class, and immigrant readers. In response, the established upper‐class journals fought back on matters of taste and politics, in part by disputing the legitimacy of the new journalism and castigating it as yellow (→ Newspaper, History of).

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.086
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.000

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 head0.018
GPT teacher head0.239
Teacher spread0.221 · 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