Adding Archival Finding Aids to the Library Catalogue: Simple Crosswalk or Data Traffic Jam?
Bibliographic record
Abstract
Dalhousie University Archives and Special Collections (DUASCSC) has been producing Encoded Archival Description (EAD) finding aids to describe its archival collections since 2003. The EAD descriptions started as a way to convert the collection of print and electronic (MS Word and WordPerfect) finding aids into a stable, software neutral format. As the collection of finding aids grew it became apparent that we needed a way to search these documents beyond what was possible via a basic browse on the DUASC website. As a result, we embarked on a systematic crosswalk of the EAD finding aids into MARC format for inclusion in the Novanet library catalogue. This has facilitated searching and discovery of the materials by a much broader audience of Dalhousie University Library users as well as users from all of the other Novanet member libraries in Nova Scotia and the general public. This article describes the primary motivation for the project and the technical aspects of converting the EAD finding aids into MARC format for inclusion in the Novanet catalogue.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.028 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".