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Record W3028173300 · doi:10.24908/iqurcp.9063

White People Ain’t Left Us Nothin’ But the Underworld: Historicity, Race and the American Dream in Ridley Scott’s American Gangster

2016· article· en· W3028173300 on OpenAlexvenueno aff
Laura Sampson

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWhite (mutation)Context (archaeology)PoliticsSociologyNarrativeMasculinityFantasyBiographyLawHistoryGender studiesArt historyPolitical scienceArtLiterature

Abstract

fetched live from OpenAlex

Released in 2007, Ridley Scott’s American Gangster tracks the career of Frank Lucas (Denzel Washington), who dominated the Harlem drug trade in the 1960s and 70s through his monopoly over heroin, which he imported directly from Vietnam and Thailand. The film follows the character of Detective Richie Roberts (Russell Crowe), who led the police task force ultimately responsible for toppling Lucas’ regime. This paper investigates the historical validity of the film, taking into consideration the consultant role Roberts and Lucas adopted during production alongside the political implications of Scott’s decision to cinematize (and so implicitly condone) the life of a convicted drug lord and accused murderer. It examines both filmic elements of music, casting and cinematography as well sociological concerns of race, space, masculinity and class in order to determine whether the film realistically portrays the lived experience of gang members and Harlem residents alike. Moreover, it considers the film’s political backdrop and its engagement with events like the Vietnam War, the Civil Rights Movement and the 1970s recession. Ultimately, the paper concludes that despite Scott’s efforts to undermine traditional iconography by portraying Lucas as a complex, rational and respected outlaw-businessman, the narrative’s lack of critical engagement with the socio-economic context of its era ultimately render it presentist in style, content and intention.

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)0.001
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: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.010
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.060
GPT teacher head0.306
Teacher spread0.246 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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