The Ukrainian Kyrylytsia, Restored: An Automation Project for Adding the Cyrillic Fields to Ukrainian Records in OCLC WorldCat
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This report from the field concerns a collaborative project which resulted in successfully adding the Cyrillic fields to about 30,000 Ukrainian bibliographic records in OCLC WorldCat, the world’s largest online catalogue. Historically, the Ukrainian records in English-speaking libraries were only provided in transliteration according to the Library of Congress Romanization Table. However, the current standards also require the original script, such as the Ukrainian Kyrylytsia. While automating the Cyrillicization of Ukrainian legacy records is theoretically straightforward, in practice it faced more than one challenge, from poor quality of transliteration to the historical changes in Ukrainian orthography. The report presents the OCLC Ukrainian Cyrillicization project and discusses the steps in its implementation as an example of a successful collaboration in the areas of bibliographic automation, Ukrainian philology and culture, Slavic cataloguing, and linguistics.
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.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it