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Record W4233069738 · doi:10.32920/ryerson.14657331

Will the real auteur please stand up!: authorship and product placement in film

2021· preprint· en· W4233069738 on OpenAlexaff
Margaret M Mohr

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicArt History and Market Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCommodificationHollywoodMovie theaterSpectacleProduct (mathematics)Product placementAuteur theoryAdvertisingAgency (philosophy)Film industryAestheticsFilm studiesArtSociologyMedia studiesBusinessVisual artsPolitical scienceLawEconomicsArt historySocial science

Abstract

fetched live from OpenAlex

This thesis investigates issues of product placement in Hollywood cinema as seen through the lenses of theories of authorship and cultural economy. Feature films, with their captive audiences and finely-tuned marketing machines, may seem like ideal venues for advertisers to present goods to consumers in the form of placed products, yet even here the effects of economic and cultural synergy cannot be guaranteed. The thesis argues that while we live in a commodified environment where the consumer spectacle is woven into the fabric of everyday life, the meanings we derive from mass-produced products is not strictly limited to the interests of corporate capital. By providing a history of product placement in Hollywood cinema and three recent films as case studies, this thesis explores the impact of product placement on the creative agency of writers, directors, designers and audiences. The thesis employs textual analysis to link theoretical issues concerning the commodification of culture and authorial expression.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.012
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.012
Scholarly communication0.0120.010
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.042
GPT teacher head0.244
Teacher spread0.202 · 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 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
Published2021
Admission routes1
Has abstractyes

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