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Global Cinema

2020· book-chapter· en· W4406694366 on OpenAlexaboutno aff
Marty Gould

Bibliographic record

VenueEdinburgh University Press eBooks · 2020
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMovie theaterArtArt history

Abstract

fetched live from OpenAlex

This essay looks beyond the film industries of Britain and the United States to investigate cinematized Dickens in its larger, global context. Looking closely at specific examples from the early silent screen through the early twenty-first century, the essay considers both how and why novels such as <italic>Oliver Twist</italic> (1837–39), <italic>Great Expectations</italic> (1860–61), and <italic>Hard Times</italic> (1854) have been cinematically translated and transformed. Cinematic adaptation both reflects and shapes different cultural readings of Dickens’s work, and films produced in India, East Asia, Africa, Canada, and Continental Europe demonstrate the availability of Dickens for modern cinematic appropriation as well as the adaptability of Dickensian characters and themes to various global cultures. Informed by current approaches to adaptation studies, the essay sketches a picture of cinematic adaptation as both interpretation and critical intervention, not merely re-presenting but translating and reconfiguring Dickens’s novels to communicate visually and to remain meaningful to diverse and evolving audiences.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.764
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.193
Teacher spread0.152 · 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
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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