Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the series Perfect Skin launched in 2015, Gregory Chatonsky, a French Canadian artist, ran an AI programme on the more than 5000 Tumblr and Instagram selfies posted by Kim Kardashian, to create distorted and serial representations of the celebrity which were then reproduced through a series of media: photo, video, textiles, ceramics, VR. Chatonsky challenges the genre of the selfie on several accounts. He highlights issues such as scale and exposure within the infoglut. Using algorithms also enables him to trigger cognitive and artistic shifts: from the visual arts to mathematics, from representation to data, from creative control to chance, from recognition to perceptual aporia, from social media to the gallery. These distorted and serialised images, “organes sans corps” to take up Deleuze’s famous concept, may pertain to a regime of meaning based on affect, as defined by Brian Massoumi, rather than on mimesis.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it