S’approprier Twitter en artiste : une pratique littéraire en question
Bibliographic record
Abstract
À travers l’étude de deux œuvres littéraires s’appropriant des tweets, I wish I could be exactly what you are looking for de Jean-Baptiste Michel et Working on my Novel de Cory Arcangel, le présent article questionne les enjeux des pratiques appropriationistes en art et en littérature à l’ère du numérique. Les œuvres sont également vues comme des portes d’entrée pour questionner les rapports de pouvoir présents dans la structuration de l’expression des utilisateurs des réseaux sociaux et que la décontextualisation des tweets nous donne la possibilité d’étudier. Elles permettent également de réfléchir sur ce que nous appelons « l’oligopole à franges attentionnel » des réseaux sociaux, structure désirant rendre compte de la distribution du capital attentionnel des internautes.
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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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.017 | 0.025 |
| Scholarly communication | 0.030 | 0.035 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".