Repositioning School Libraries towards Attainment of Learning without Borders
Bibliographic record
Abstract
The internet has revolutionized the global world system. Every aspect of the globe is under the influence of information and communication technologies. The educational sector is experiencing a paradigm shift towards a borderless economy and school libraries occupy a central place in the actualization of sustainable education. The paper highlights the need to reposition school librarianship to ensure actualization of learning without borders, the significance of school libraries in learning without borders agenda. Repositioning of school libraries requires addressing personnel issues, ICT-related issues, funding, extensive lobbying and advocacy, partnership with NGOs and stakeholders in educational sector, recruitment of qualified library staff and re-training of existing school library staff to meet global realities.
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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 | 0.023 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.031 | 0.026 |
| Open science | 0.003 | 0.029 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 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".