Contextualizing the Transformed Roles of the School Librarian and Library: A Case Study to Inform LIS Education
Bibliographic record
Abstract
Accredited school library educator preparation programs are responsible to align their curriculum to the American Association of School Librarians Standards for the Initial Preparation of School Librarians (2010). These standards include Teaching for Learning, Literacy and Reading, Information and Knowledge, Advocacy and Leadership, and Program Management and Administration. To keep more current with the actualities of the profession, the AASL recently released new National School Library Standards for Students, School Librarians, and School Libraries (2018). In the document, the roles and responsibilities of school librarians have been reexamined. A challenge for school library educator preparation programs is keep up to date with the changes to ensure a curriculum that prepares graduates with the relevant knowledge and skills to be effective school librarians. This study will help LIS schools by examining the attributes of a high-quality school library program in practice.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.026 | 0.012 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".