Collections of the Library and Archives of Canada as a sourse base for scientific research on the history of Ukraine
Bibliographic record
Abstract
The article examines the collections of the Library and Archives of Canada, which cover the materials of the historical and documentary heritage of the country. The experience of the Library and Archives of Canada in structuring and organizing information resources on Ukrainian studies and search capabilities of the electronic catalog was analyzed. It was found that organized information arrays of thematic orientation form the source base for research in various disciplines, including Ukrainian studies. Collections and databases containing information resources on Ukrainian culture and history, including unique archival documents on the history of Ukrainian immigration to Canada, are considered. It is noted that providing access to databases of different thematic orientation allows the user to limit the search to a particular industry. It is emphasized that the Library and Archives of Canada play an important role in preserving Ukraine's historical and cultural heritage and disseminating knowledge about Ukraine. It was found that the provision of a set of navigation and search tools to ensure access to historical and cultural heritage and scientific heritage, the use of special thematic collections and databases in research and teaching and presenting them on the library website increases the role of the library and significantly increases efficiency of scientists' work. It is emphasized that it is expedient and useful for scientific libraries to study the experience of libraries in the world in structuring and organizing information resources on national issues.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.016 | 0.043 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".