Bibliographic record
Abstract
En 2002 a été publié pour la première fois le « power 100 », classement annuel des personnalités du monde de l’art les plus puissantes. Réunissant quelques artistes mais aussi des galeristes, directeurs de maisons de ventes aux enchères, collectionneurs, directeurs et conservateurs de musée, commissaires et critiques, ce palmarès peut faire l’objet d’une analyse sociologique. Position ou fonction dans le monde de l’art, genre (homme ou femme) mais aussi pays d’appartenance constituent trois facteurs importants pour mieux comprendre comment le pouvoir s’organise dans le monde international de l’art contemporain. Par ailleurs, dans la mesure où ce palmarès censé révéler le pouvoir dans le monde de l’art — impliquant tout particulièrement celui de labelliser et consacrer les artistes — existe de façon concomitante aux classements d’artistes les plus reconnus, il devient possible de tester l’hypothèse d’homologie bourdieusienne entre caractéristiques de ceux qui construisent les réputations et ceux qui les obtiennent, les artistes.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".