Efforts and Changes Around School Libraries in Sweden Today: When Great Things are Happening… How Do We Communicate with Authorities and Decision Makers?
Bibliographic record
Abstract
As the IASL conference themes in Long Beach (2017), Istanbul (2018), and Dubrovnik (2019) have influenced progression, impact, and innovation around school libraries, it is interesting to focus on how ordinary school librarians best adopt fields where communication on a higher level marks the spot! The theme for this paper will work as a useful contribution to different methods, practically applied in Sweden for over ten years. Methods of communication that function as an inspiration to the higher governmental work and processes for school libraries, both on a national and international level. A wider scale on the following topics will be presented - mainly to create a developed knowledge adapted for school libraries. Knowledge ready to be transformed when participants return to their homes, communicating with their own contacts responsible for school libraries.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.034 | 0.017 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".