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Deconstructing the “War of All Against All”: The Prevalence and Implications of War Metaphors and Other Adversarial News Schema in TIME, Newsweek, and Maclean’s

2005· article· en· W767988052 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

VenuePeace and Conflict Studies · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAdversarial systemSchema (genetic algorithms)Period (music)Spanish Civil WarPolitical scienceMedia studiesSociologyLawAesthetics

Abstract

fetched live from OpenAlex

This study examines and critiques the discursive construction of a Hobbesian “war of all against all” in North American commercial news magazines. The prevalence of war metaphors and related adversarial news schemas is documented over a twenty year period, from 1981 to 2000, through an analysis of TIME and Newsweek, along with their Canadian counterpart Maclean’s. After documenting the pervasiveness of these discursive constructs, the paper discusses the underlying causes and potential consequences of these patterns in commercial news discourse. The paper concludes by asserting that this discursively constructed “war of all against all” is highly problematic and unsustainable in an age of increasing social and ecological interdependence. Accordingly, scholars who are interested in peace and conflict resolution would do well to take into account the role that news discourse and other forms of mass-mediated communication play in the perpetuation of social conflict.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.394

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.304
Teacher spread0.228 · 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