MétaCan
Menu
Back to cohort
Record W2997548104 · doi:10.1080/17411548.2019.1708037

<i>Boy 7</i> in double exposure: European genre cinema between transnational industry practices and national consumption

2019· article· en· W2997548104 on OpenAlexaff
Gabriele Mueller

Bibliographic record

VenueStudies in European Cinema · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsYork University
Fundersnot available
KeywordsMovie theaterAppealGermanFilm industryConsumption (sociology)National cinemaFilm studiesAudience measurementMedia studiesSociologyAestheticsAdvertisingPolitical scienceVisual artsLawArtHistoryBusiness

Abstract

fetched live from OpenAlex

This article examines two film adaptations of the same novel as a media strategy that takes advantage of transnational film industry practices and infrastructure in order to produce films for targeted national consumption. In 2015, two film adaptations of the Dutch YA (Young Adult) novel Boy 7 by author Mirjam Mous were in production simultaneously, one a Dutch production by Lemming Films, the other a German-language version produced by Hamster Film, Lemming’s German sister company. The source novel, a science fiction thriller in the vein of texts such as The Hunger Games, had been very successful with a teenage readership in both countries because of its transnational characteristics and global appeal. The article discusses the film adaptations of Boy 7 as a case study that illuminates the continued positioning of European genre cinema as part of national film traditions. I argue that this position is mainly industry driven and a result of commercial concerns, but it also reveals the tensions between, on the one hand, increasingly transnational industry practices and, on the other, the persistence of cultural specificity and the need to appeal to local and national audiences whose tastes are being shaped by global cinema.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.381
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.133
GPT teacher head0.391
Teacher spread0.258 · 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 designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueStudies in European CinemaSame topicDigital Games and MediaFrench-language works237,207