Misère symbolique ou émancipation des systèmes de représentation
Bibliographic record
Abstract
Ce colloque porte sur les systèmes de représentation d’institutions publiques à grandes échelle : collectivités, états, institutions culturelles, hôpitaux, universités, etc. Les identités visuelles de ces institutions empruntent bien souvent les logiques de la marque, sur le modèle des sociétés commerciales. Mais le logotype est-il pour les institutions la seule manière d’exister dans l’espace public ? Ces systèmes de représentation permettent-ils l’exercice de la citoyenneté ? Comment le design graphique peut-il représenter la complexité de ces ensembles ? Intervenants : Violaine Appel, Vera Baur-Kockot, Alain Beretz, Nawal Bakouri, Laurie Chapotte, Xavier Crouan, Julien Defait, Olivier Deloignon, Michel Deneken, Bernard Emsellem, Martin Grandjean, Etienne Guidat, Pierre-Damien Huyghe, Jean-François Lanneluc, Claire Laval, Malte Martin, Dominique Mégard, Faustine Najman, Daniel Payot, Christina Poth, Franck Tallon, Armelle Tanvez, Fabrice Papy, Philippe Portelli, Armelle Tanvez, Cécilia Zanni-Merk
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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.018 | 0.021 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".