Domestic and Foreign Experience in Forming of Documental Flow in Scientifi c Libraries Under the State Publishing Programs
Bibliographic record
Abstract
The article highlights cooperation of V. I. Vernadsky National Library of Ukraine and State Committee for television and radio broadcasting of Ukraine as part of state program «Ukrainian Book», which was founded with the initiative of the President Victor Yushchenko in 2005. Main theme directions for book publishing are: editions for children and youth; works of Ukrainian literature classics, winners of Shevchenko National Prize and modern Ukrainian writers; works of classical and modern writers of foreign literature (in Ukrainian); non-fiction editions; reference editions; the literature in minorities languages of Ukraine. This is a budgetary program, and according to it state order on printing of publishing products and it’s distribution amongst libra- ries of Ukraine is made. The list of books is formed by State Committee for Television and Radio-broadcasting of Ukraine. The article presents the dynamics of literature receipt from a «Ukrainian Book» program to current exchange fund of V. I. Vernadsky National Library of Ukraine in 2007-2016 years. Since 2017 all of the rights on book printing from this program were transferred to Ukrainian Book Institute. The work also contains foreign experience of similar institutions in Poland, France, Canada and Finland, and its activity aimed at popularization of reading, distribution of books, promotion of national literature and home language in the world.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".