Expanding the Range of Evidence Use in School Library Practice
Bibliographic record
Abstract
The study explores the involvement of school librarians from Croatia and Hong Kong in EBLIP. The main goal of this study is to find out what types of evidence school librarians from Croatia and Hong Kong use in their library practice and how useful they find different evidence types. The research method used in this study is survey and data were collected with an online questionnaire created and delivered with SurveyMonkey. The study reveals that school librarians in Croatia and Hong Kong use a wide variety of evidence sources in support of their library practice. Most often they use evidence from observation, professional interactions and library statistics. School librarians in both regions agree that these three types of evidence are the most useful for their library practice. However, if school librarians wish to demonstrate to stakeholders how school libraries contribute to teaching and learning they need to generate some more objective evidence through formal research. LIS educators and local school library associations may be encouraged to develop educational programs that will enhance school librarians' competences in formal research and involve them in a participatory research community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".