Florida’s School Library Programs and Achievements: What Can Be Adopted in the Brazilian Context
Bibliographic record
Abstract
What motivated this research was the Brazilian law promulgated in 2010 stating that in 10 years all Brazilian schools should have school libraries. 24 American school librarians were interviewed with the aim of learning from their professional experience the most important points that could be extended to Brazil via transferability of models of organizing and conducting school libraries. Results were coded and categorized. One of them showed that Florida's programs to promote reading were effective, with the participation of most the librarians interviewed. Librarians demonstrated both their involvement in the book selection committees as their enthusiasm in engaging the kids. Getting children to be long life readers was stated as important for at least half of the interviewees. Since Brazilian libraries are failing in this first aspect of their role, this paper focuses on the importance of forming school librarians themselves as readers, so they can become good reading mediators.
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".