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Record W2800660771 · doi:10.3138/cjfs.19.2.2

“Until Justice is Done”: Authenticity and Memory in Paul Greengrass’s <i>Bloody Sunday</i> and <i>United 93</i>

2010· article· fr· W2800660771 on OpenAlexvenueno aff
Duncan Greenlaw

Bibliographic record

VenueCanadian Journal of Film Studies · 2010
Typearticle
Languagefr
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesEconomic JusticePolitical scienceArtEthnologySociologyLaw

Abstract

fetched live from OpenAlex

Établissant des liens entre les visées des représentations politique et cinématographique dans les films de Paul Greengrass Bloody Sunday et United 93, cet article pose la question de ce que signifie « faire justice » à des événements nationaux traumatiques. Les stratégies du réalisateur pour faire justice à ces événements en capturant authentiquement aussi bien l’histoire que les identités culturelles des sujets impliqués (les soldats britanniques et les manifestants républicains en 1972 et les passagers et les pirates de l’air en 2001) font écho à des distinctions théoriques non résolues du travail de Derrida et Benjamin, entre la loi et la justice, entre les conceptions auratiques et non-auratiques de l’art et entre la mémoire volontaire et non volontaire. Oscillant d’un pôle à l’autre de ces oppositions, les films démontrent comment les récits de l’authenticité et de la justice excèdent les présuppositions mêmes sur lesquelles ils reposent. Mais encore, ils révèlent aussi que, dans cet échec pour rendre compte de l’histoire, un genre particulier de « justice disjonctive » émerge — un qui anticipe la réévaluation créative et la remémoration continue des événements traumatiques.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.270
Teacher spread0.227 · 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 teacher head, not a consensus.

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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