State of Art Museum Libraries, 2024
Bibliographic record
Abstract
The State of Art Museum Libraries 2024 Task Force built on the foundational work presented in the State of Art Museum Libraries 2016 White Paper, which detailed the roles, issues, and challenges faced by art museum libraries in the United States. Now, five years after the onset of the COVID-19 pandemic, an event that has profoundly reshaped practices across the library field, the State of Art Museum Libraries 2024 report presents new research carried out by the task force that assessed the current state of museum libraries in the United States and Canada. The State of Art Museum Libraries 2024 report presents findings from the field level survey completed by 61 museum libraries and discusses key findings, including the evolving role of libraries within art museums, institutional support for museum libraries, staffing and hiring practices, work-life balance and workplace culture, the state of diversity, equity, and inclusion initiatives, collection development and management, and emerging trends in user experience. The report's appendices include the task force's survey instrument, a list of art museum libraries that received the survey, and the survey data.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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".