Expanding access to Nickolas Muray's celebrity portraits: cross cataloguing of Richard and Ronay Menschel Library manuscript and photography collections at George Eastman House
Bibliographic record
Abstract
This applied thesis project was undertaken to expand access to the photographer Nickolas Muray’s (1892–1965) celebrity portraits by creating intellectual links between the Richard and Ronay Menschel Library Manuscript Collection and the Department of Photography (DOP) Collection held at George Eastman House International Museum of Photography and Film, Rochester, New York. The project consisted of two phases: (1) to create item-level descriptions for the published examples of Muray’s celebrity portraits in the Library’s Nickolas Muray Manuscript (Mss) Collection Boxes 125-126 Illustrations, and (2) to revise the DOP catalogue records for the corresponding photographic prints and negatives, and their variants from the same photographic sessions within the museum’s collections management system, The Museum System (TMS). This paper outlines the methodologies behind the project and describes decisions made to expand access to Muray’s celebrity materials in both the manuscript and photographic collections.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 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; 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".