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Record W4200492824 · doi:10.1177/17506352211059130

Iconic war images and the myth of the ‘good American Soldier’

2021· article· en· W4200492824 on OpenAlex
Megan MacKenzie

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedia War & Conflict · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsSimon Fraser University
FundersDanmarks Frie Forskningsfond
KeywordsMythologyMasculinityNarrativeIdeal (ethics)VirilitySociologyGender studiesAestheticsWhite (mutation)Identity (music)RomanceNationalismHistoryLiteratureArtPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

This article explores the ‘good American soldier’ as a gendered ideal type shaped by, and reproductive of, myths about American military success, romantic notions of small-town working and white America, notions of heterosexual virility, and ableist stereotypes about personal resilience. Drawing from an analysis of 10 years of media coverage of an iconic image dubbed the ‘Marlboro Marine’, the article outlines three specific myths linked to the ‘good American soldier’, in order to provide an insight into ideals of militarized masculinity and the gendered myths that shape American nationalism and identity. In developing this analysis, the article extends existing work on military masculinities by introducing the ‘good American soldier’ ideal type and explores the multiple myths associated with this ideal type. The article also demonstrates how a media narrative analysis that covers an extended period of time makes it possible to observe shifting narratives associated with the ‘good American soldier’.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.864
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.274
Teacher spread0.255 · 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