Metadata for phonograph records : facilitating new forms of use and access
Bibliographic record
Abstract
This dissertation presents a new metadata design, as part of a large digitization management system being developed, to assist in the consistent creation of digital libraries of phonograph records. The Metadata provides digital libraries with an effective tool for the description, discovery, management, control, delivery, and sharing of digital objects of phonograph record. The metadata design is the outcome of two pilot projects for the digitization of phonograph records that took place at the Marvin Duchow Music Library at McGill University. The new design offers an approach to maintaining and using digital sound and ensures the long-term viability of digital libraries of phonograph records. The dissertation discusses key areas of preservation and addresses the most common retrieval problems of music in digital libraries. These problems include challenges in the digital context of bibliographic control, cataloging, distribution, and copyright protection. The dissertation revisits traditional cataloging approaches, summarizes historical music cataloging and metadata development, sets up preservation principles and rationales for digitizing phonograph records, and presents state-of-the-art techniques for preserving phonograph records in the digital domain. The dissertation contains three main parts. The first is an introduction to the new metadata design for phonograph records. The second is a metadata dictionary, which assigns precise syntactic and semantic meanings to metadata elements, to guide digitizers working in libraries, archives, museums, and heritage sectors. These will be followed by two case studies of phonograph record digitization projects using the Metadata and the Data Dictionary. The dissertation concludes by examining three challenges that are critical to future development in both the preserving of and access to phonograph records: the issue of interoperability between different metadata standards, the need for usability and quality evaluation of digitization management systems, and the importance of further development in digital library retrieval services and tools.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.015 | 0.038 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".