Bibliographic record
Abstract
As the 2017 IASL conference theme will be “Learning without borders” it is interesting to focus on how the school library, as well as the school librarian, will have to adopt the field – to establish and develop the field as a whole. By describing the whole field, with a perspective taken from the Swedish school library, from the present situation 2016/2017 and even further than that, there will be a contribution of useful material and methods – inspirational to the work and progress for school libraries/school librarians. Three specific subjects will be presented during the lecture - mainly to create a sustainable knowledge on school libraries as a learning tool in school - with a special focus on the political and structural efforts/changes taking place in Sweden today. The three specific subjects are: the Swedish National Agency for Education, The national school library group of Sweden (NSG), School Library West (SBV).
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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.038 | 0.017 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".