Bibliothèques de musées, bibliothèques universitaires : des collections au service de l’histoire de l’art
Bibliographic record
Abstract
By moving into the Labrouste reading room, the library of the Institut national de l’histoire de l’art will fulfill years of preparation, reflection, and debates that have punctuated its long gestation. As a descendant of the Bibliothèque d’art et d’archéologie Jacques Doucet, its affiliation with the university is today lively and meaningful. The incorporation of the Bibliothèque centrale des musées nationaux, formerly at the Louvre, on January 1, 2016 has invited museums into the heart of INHA’s collections. For the three entities concerned, this change has involved – and still involves – a questioning of the orientation and missions of the libraries they represent. The Louvre museum has launched a vast project of promotion and coordination of its libraries. After extensive preparatory work, the Bibliothèque centrale des musées nationaux (BCMN) has been physically absorbed into the INHA, requiring a necessary examination at the INHA, not only of its history, but also of its project. Indeed, for the INHA library, the foundation stone that is the BCMN consolidates this inauguration in completely renovated spaces: a reading room with four hundred seats, together with open-access stacks containing 150,000 documents on three levels, opening with the Bibliothèque nationale de France and in particular its département des Estampes et de la photographie, but also with the École nationale des chartes. The three texts that follow must therefore be read interactively as exchanges relating to what makes writing the history of art possible.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.023 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.033 | 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; 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".