What happened to the subject? Mediated anticipation in neural painting
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
This article presents a phenomenology of artistic painting as an anticipatory process. I propose that the artist seeks to establish a state of equilibrium in a model of self-awareness expressed and represented in a self-constituted physical artefact intended to communicate to others, not representationally but affectively. ‘Neural painting’ is an arts-based research method employing a simple computational model of human aesthetic discrimination to study the creative realization of the artistic image. I use this method to explore the relationship of self and ‘other’ in computationally mediated self-portraiture. I develop an image in an exchange with a neural network by reflecting on its output and inputting autographic modifications to those images, blending visceral gesture with the ‘black box’ of artificial intelligence. Through this deeply personalized and perhaps agonistic interchange between organic self and algorithmic reflection, I seek to expose the tacit mediation implicit in the technical artefact, opening an understanding of the existential relations between natural systems (the artist) and technical entities positioned as collaborators in an anticipatory aesthetics .
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it