MétaCan
Menu
Back to cohort
Record W1645508814

Fitzgerald’s The Great Gatsby Between the Film and the Novel: A Corpus-driven Study of Students’ Responses

2011· article· en· W1645508814 on OpenAlexvenueno aff
Nazmi Al-Shalabi, Fahed Salameh, Marwan M. Obeidat

Bibliographic record

VenueStudies in literature and language · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature, Film, and Journalism Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsScripting languageKey (lock)PsychologyAestheticsSociologyLiteratureArtComputer science
DOInot available

Abstract

fetched live from OpenAlex

It is argued that films are valuable parts of our culture, that they facilitate students’ understanding of novels, that they make classes more interesting, and that they should be integrated into the course materials. In line with this contention, this article attempts to explore the significance of film as an educational tool from the students’ perspectives. Students have been given a question focusing on their impressions about the novel and the film. They have been also given a week’s reprieve to turn in their responses via e-mail so that they can maintain the necessary privacy and answer freely. In this way, they won’t be obligated to choose a given response similar to what occurs in a questionnaire. The discussion demonstrates that most students are not for watching films, and that their responses are indicative of their uncritical viewing of the film. Having no clear idea about cinematic techniques and directors’ treatment of texts and changing them into scripts, students are not in a position to evaluate films well. Key words: Albinism (albino); Race; Blackness; Community; John Edgar Wideman

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.052
GPT teacher head0.299
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueStudies in literature and languageSame topicLiterature, Film, and Journalism AnalysisFrench-language works237,207