Bibliographic record
Abstract
Our school faced a particular problem. As in many other schools, teachers and students are increasingly mobile savvy and internet connected while at school. This affects how teaching is done and how libraries are used. In response proposed to bring the Library to the classrooms. We would move the existing library, from its own building, to share the center of the action, into learning spaces once occupied only by classrooms. While the digital integration had already begun, the physical integration would serve both the traditional and new ways in which libraries can be used. We propose that both library and classroom practices will be “flipped” so that putting ideas and information into action and thinking about what you have learnt will become the focus, using the new library to extend and enrich that practice. This paper will report on the practical implications and experiences of such an undertaking. In addition, the paper will outline some of the research concerning how the elements of the learning process are distributed across the day.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.024 |
| Scholarly communication | 0.019 | 0.025 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.037 | 0.012 |
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".