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Record W2046007219 · doi:10.7202/1025926ar

Avoir une voix dans sa propre histoire. Féminité, care et sexualité dans Irina Palm de Sam Garbasky

2014· article· fr· W2046007219 on OpenAlexvenueno aff
Pascale Molinier

Bibliographic record

VenueRecherches sémiotiques · 2014
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanitiesPolitical science

Abstract

fetched live from OpenAlex

Cet article se penche sur le film de Sam Garbarski, Irina Palm (2007). Un petit garçon, Ollie, est gravement malade et le coût du traitement dépasse les moyens financiers de sa famille. Pour amasser la somme, Maggie, sa grand-mère, se fait embaucher dans un sex-shop où, cachée derrière un mur, elle masturbe à la chaîne des clients. Satisfaite, la clientèle se multiplie et les hommes sont bientôt légion à fréquenter son isoloir et à fantasmer être livrés aux mains expertes d’une créature merveilleuse nommée Irina Palm. L’expérience de Maggie, qui pourrait être vécue comme une décrépitude morale, devient au contraire une occasion de perfectionnement. En s’occupant des autres et de son travail, elle devient à nouveau désirable et libre pour la première fois de sa vie. L’actrice Marianne Faithfull, qui l’incarne, sert au public féminin une leçon de vieillissement. Ce film traite du travail du care, du travail domestique et travail sexuel dans un continuum, dans la lignée du mythique Jeanne Dielman (1975) de la réalisatrice belge Chantal Akerman.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.007
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0020.005
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 head0.095
GPT teacher head0.416
Teacher spread0.321 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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