Bibliographic record
Abstract
Cet article se concentre sur un des tropes majeurs du témoignage audiovisuel : le visage. Il s’agit de réfléchir, dans le contexte de la violence de masse, à la façon dont le visage cristalliserait l’image-témoin elle-même. Pour ce faire, deux installations vidéo sont prises en compte : Entre l’écoute et la parole : derniers témoins. Auschwitz-Birkenau 1945–2005 (2010) de l’artiste Esther Shalev-Gerz et Chorus (2015) du cinéaste Atom Egoyan. Les deux artistes touchent, respectivement, à la Shoah et au génocide des Arméniens en multipliant les écrans par lesquels les visages des survivants (réels ou fictifs) apparaissent comme les seuls possibles loci du témoignage indicible. Parallèlement, l’article insiste sur la pertinence de la pensée du philosophe Emmanuel Levinas lorsqu’on invoque la relation entre image et témoignage au-delà des régimes représentationnels et spectatoriels. Au bout du compte, on tentera de désacraliser et de décaricaturer le visage comme figure démonstrative et dévoilante (souvent typique du témoignage audiovisuel), afin de révéler l’infini glissement qui singularise l’image-témoin.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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; both teacher heads agree on what is shown here.
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".