Reading communities in the School Library: the role of web 2.0 and social media
Bibliographic record
Abstract
Literature for children and young people is taking advantage of the dynamics offered by digital world. Web tools and social media are now powerful resources to promote reading and children's literature among the new generations. These tools, due to its interactivity, open the door to new readers that find a new appeal when interacting with literature through these tools. Taking into account this context, school libraries cannot stay apart from the possibilities that these resources can offer for reading promotion. So, in Portuguese school libraries several projects are being developed, based on the dynamics that web 2.0 tools offer. In this paper we present some results of a project developed under a master's degree in School Libraries, at the Portuguese Open University. The results of these studies show a diversity of strategies that are followed by school libraries, trying to involve various actors (teachers, students, parents), thus contributing to the development of reading skills, with positive effects on motivation, reading and writing interests and competences.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".