Towards a Transformative Pedagogy for School Libraries 2.0
Bibliographic record
Abstract
As more and more educators face the impact of Web 2.0, and as we see emerging what could be called a Learning 2.0 environment, it becomes urgent to extend teaching to meet the literacy and learning needs of the Net Generation. These new learners and their expanding literacy needs have major implications for current models of school library programs hich are largely focused on reading promotion and information literacy skills. We join others in recognizing the need to critically question long held tenets of school libraries and to create a new research-based vision that will accord with the current economic and social directions driving educational change. This paper contributes to that process by proposing a ramework for the work of school libraries in new times based on research in new literacies, today's learners, and emerging concepts of knowledge.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.009 | 0.028 |
| Scholarly communication | 0.018 | 0.020 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".