Nomenclature 4.0 for Museum Cataloging
Bibliographic record
Abstract
Nomenclature 4.0 for Museum Cataloging is an updated and expanded edition of Robert G. Chenhall’s system for classifying human-made objects, originally published in 1978. The Chenhall system is the standard cataloging tool for thousands of museums and historical organizations across the United States and Canada. For this fourth edition, hundreds of new terms have been added, and every category, class, sub-class, and object term has been reviewed and revised as needed by a professional task force appointed by the American Association for State and Local History. This new edition features crucial revisions including: • A revised and updated users’ guide with new tips and advice • An expanded controlled vocabulary featuring nearly 950 new preferred terms • 475 more non-preferred terms in the index • An expanded and reorganized section on water transportation • Expanded coverage of exchange media, digital collections, electronic devices, archaeological and ethnographic objects, and more AASLH has developed a free online community for all users and potential users of Nomenclature 4. Click here to access the Nomenclature 4.0 online community .Use this site to learn about Nomenclature 4.0, to share news and ask advice, and to submit your own proposals for additions and changes for future editions.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.018 | 0.024 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.023 | 0.020 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.617 | 0.743 |
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".