Bibliographic record
Abstract
This chapter presents a year-long collaboration by two editors, one in Italy and one in Canada, that resulted in 2011 the IFLA Publication No. 148, titled Global Perspectives on School Libraries: Projects and Practices. Supporting the work of the two editors were the members of the Joint Committee of two international school library groups, the School Libraries and Resource Centers Section of the International Association of Library Associations and Institutions (IFLA SLRC) and the International Association of School Librarianship (IASL), and the staffs of IFLA Headquarters and of IFLA’s publisher, De Gruyter Saur. The 300-page book included 30 chapters, written by 50 authors from 20 countries across 6 continents. The topics addressed in the book included: school library education and implementation models; promoting literacies through the school library; school libraries for all; expanding the reach of the school library through technology; government initiatives for school library development; and organizations for school library advocacy and development. The whole process—from designing the publication to disseminating it—is described, including some lessons learned along the way, useful for planning joint work of a similar nature. Future steps in the collaboration between the IFLA SLRC Section and IASL collaboration are introduced as well.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.029 | 0.020 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.040 | 0.013 |
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".