Empowering School Libraries through International Projects
Bibliographic record
Abstract
School libraries have no limits, no boundaries, not even for those in rural areas, where cultural opportunities are scarce. In such cases, school libraries themselves become THE opportunities, THE hearts/souls of institutions, HOME for students and teachers engaged in a major journey with other European fellows. This is the story of “Yourope: You in Europe”, an Erasmus KA2 project, which, dear reader, you are about to get familiar with. By enrolling in international projects, you empower your school library and leave traces in your institution and in the citizenship sense of students. The use of the English language comes in a natural way; new ICT tools are used not as an end in themselves, but as a means to achieve certain purposes; the school library resources become fundamental to accomplish the planned tasks. Why did we choose the theme “Europe”? As we will explain in this article… because Europe is all about you and me, and not somebody else.
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.
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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.028 | 0.026 |
| Open science | 0.001 | 0.045 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".