Bibliographic record
Abstract
Although most art museums possess a library of some kind, these facilities are often hidden from the public and seldom discussed in library schools despite the important role they play as substantial research venues. Co-published with the Art Libraries Society of North America,Art Museum Libraries and Librarianshipserves as an introduction to the field of art museum librarianship and its diverse settings. Editor Joan Benedetti has compiled contributions from practicing art museum librarians to present sixteen chapters that address the topics of leadership, reader services, automation, security, cataloging, space planning, collection development, visual resources, ephemera, special collections, archives, fundraising, public relations, volunteers and interns, professional development, and solo librarianship. Each chapter consists of several essays that deal with the distinct environment of art museum libraries: from the largest research collections that serve many curatorial departments and multiple administrative layers to the smallest solo librarian venues whose unsung staff work in relative isolation. The book concludes with a collection of brief institutional profiles, which include statistical and descriptive information on fifteen diverse art museum libraries in the U.S., Canada, and Europe; appendixes that describe academic programs offering dual degrees in librarianship and art, list international professional associations for art museum librarians, and provide sample policies and procedures in use today in art museum libraries; a bibliography; and an index. Art Museum Libraries and Librarianship, the first publication of its kind, is illustrated with over 90 black and white images of art museums, their libraries, and items from their collections.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.046 | 0.018 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.058 | 0.033 |
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".