The Role of Libraries as Publishers in the Open Education Landscape: Reflecting Modern World Practice of Open Textbooks
Bibliographic record
Abstract
Objective. The study aims to analyse the experience of university libraries in different countries in working with the Open Textbook (OT) and to consider the prospects of creating a similar pilot project in Ukraine. Methods. The analysis covered the world publications (journals, books, conference proceedings, posts on social networks) in the field of Library and Information Science, devoted to the role of libraries in OT support, that have appeared since 2014. The author studied the aspects revealing that publication, namely OT, support services are areas with great potential for the future development of academic / university libraries. Results. Numerous evidence is presented that the topic of library as a publisher in OT support is most developed in the universities and colleges in economically developed countries, especially in the USA, Canada, Australia, and Great Britain. Library strategies for OT projects have been identified. The author clarified the nature of the initiatives and partnerships of libraries in supporting OT, as well as the basic services and roles of libraries in these projects. Conclusions. Today, the global practice of Scholarly Communication has enough evidence that the functions of the Library, lost in the course of evolution, as a Knowledge Publisher have returned under its “roof” and supplemented the existing function of Knowledge Managers. Digital Library Publishing (DLP) services in OT support help to change the learning environment and life of students (including persons with disabilities), pedagogical practices of teachers by means of free textbooks with an open license, as well as to receive reputation benefits for the university, improving the image of the latter. The possibility of eliminating systemic inequalities in access to academic resources increases the significance and changes the role of libraries in open education. The successes of Ukrainian librarians in supporting digital scholarly communication initiatives and the successful implementation of Open Access support projects (repositories, e-journals, e-conferences) give confidence that they can act as initiators and key partners in creating affordable textbooks.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.039 | 0.023 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".