Vers un commun numérique de l’art public
Bibliographic record
Abstract
En 2023, la Maison MONA, un OBNL culturel, met en place une initiative sur les données ouvertes et liées dans le secteur de l’art public. Le projet entrepris entend explorer les usages et les possibilités des LOD, en identifiant les initiatives actuelles, les besoins et les enjeux propres au secteur de l’art public, les défis spécifiques à la structuration et à l’utilisation de données culturelles, et en sensibilisant les artistes et les travailleur·euse·s culturel·le·s aux bonnes pratiques. Le dossier « Vers un commun numérique de l’art public » vise à documenter le déroulement de ce projet. Ce premier article en présente la genèse et les objectifs,avant de s’attarder sur son point d’ancrage, les plateformes Wikidata, Wikimédia Commons et Wikipédia.
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 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 | 0.001 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.008 |
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; both teacher heads agree on what is shown here.
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".