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Record W4388112714 · doi:10.1386/jepc_00056_7

‘A normal life’: Karel Tuytschaever on the dramas of Easy Tiger

2023· article· en· W4388112714 on OpenAlexaff
Tom Ue

Bibliographic record

VenueJournal of European Popular Culture · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicVisual Culture and Art Theory
Canadian institutionsDalhousie University
Fundersnot available
KeywordsKarelFilm directorSilenceFeelingScholarshipShort FilmSociologyMovie theaterAestheticsVisual artsPsychoanalysisTigerArtMedia studiesPsychologyArt historyLawPolitical scienceSocial psychologyComputer science

Abstract

fetched live from OpenAlex

In this interview, actor–director Karel Tuytschaever and I examine his first feature film, a critical-creative project entitled Easy Tiger (2022). In it, the meeting between a psychologist (Mickaël Pelissier) and his client (Casper Wubbolts), a deaf man, proves revelatory for them both. The client speaks of a dying man with whom he was deeply in love, which leads him to explore his feelings about the possibility of finding true love. These confessions prompt the psychologist to re-evaluate his relationship with himself and with the world. Tuytschaever and I discuss how he brings together his roles as a director, an actor and an academic, before examining the film and how he communicates his complex vision with us and with his actors. Much of the film involves stillness, and it unfolds in silence. We discuss how Tuytschaever speaks volumes with it, making the film of significant interest for both hearing and other/non-hearing people. Easy Tiger received an Honorable Mention as Indie Feature Film in the Paris Film Awards; and it has earned Best Queer, Best Directing and Best International Film awards at the SENSEI FilmFest. This interview advances scholarship by introducing us to Tuytschaever’s critical work and by examining how it informs his artistic project.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.459
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.001

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 head0.044
GPT teacher head0.245
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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