On the Wandering Cephalophore: Stiegler and Serres’s <i>Tête-à-Tête</i>
Bibliographic record
Abstract
The motivation for this experimental writing arose from encounters with sculptures during dérive exercises in various cities in 2022 and 2023. A profound experience in Argentina transformed my aesthetic sense into a political one ( aisthēsis, the mattering of sensation), leading me to explore the plastico-pedagogical uses of sculpture. I began to wonder how urban wandering can mould subjectivity and how the city can become a plastic canvas for philosophical thought. Inspired by Michel Serres’s Thumbelina (or Petite Poucette, as it appears in the French edition) and Bernard Stiegler’s ideas, I reflected on smart cities, artificial intelligence, and the therapeutic use of technology during these wanderings. Through Félix Guattari’s interpretation of “modelling clay,” I argue that the urban milieu can reshape subjectivity in both poisonous and curative ways. My thought experiment reconsidered the practice of psychogeography as a way in which to transform the smart city into a subjective city.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".