A Mode of Agitation between <i>Verfremdungseffekt</i> and Empathy: Breaking the Fourth Wall in Craig Gillespie’s <i>I, Tonya</i>
Bibliographic record
Abstract
Le présent article analyse le film Moi, Tonya (Craig Gillespie, 2018) en se penchant particulièrement sur la technique théâtrale d’adresse directe à la caméra. Cette méthode crée un mode d’agitation qui fluctue entre l’effet de distanciation de Brecht et l’empathie. L’utilisation de gros plans faciaux, de zooms et de travellings dans des espaces intimes suscite des émotions chez l’auditoire à travers un récit alternatif de Tonya Harding. Cependant, les scènes sapent continuellement la confiance ainsi développée à travers le témoignage contradictoire et la figure de Tonya désignant le téléspectateur comme étant son « agresseur ». Moi, Tonya s’attaque de façon agressive aux répercussions sociales et politiques à plus grande échelle de la violence conjugale dans les ménages de faible statut socioéconomique aux États-Unis, la consommation médiatique dénuée de toute critique et les structures capitalistes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".