Bibliographic record
Abstract
When Su Cleyle and I first decided to start Evidence Based Library and Information Practice, one of the things we agreed upon immediately was that the journal be open access. We knew that a major obstacle to librarians using the research literature was that they did not have access to the research literature. Although Su and I are both academic librarians who can access a wide variety of library and information literature from our institutions, we belong to a profession where not everyone has equal access to the research in our field. Without such access to our own body of literature, how can we ever hope for practitioners to use research evidence in their decision making? It would have been contradictory to the principles of evidence based library and information practice to do otherwise.One of the specific groups we thought could use such an open access venue for discovering research literature was school librarians. School librarians are often isolated and lacking access to the research literature that may help them prove to stakeholders the importance of their libraries and their role within schools. Certainly, school libraries have been in decline and the use of evidence to show value is needed. As Ken Haycock noted in his 2003 report, The Crisis in Canada’s School Libraries: The Case for Reform and Reinvestment, “Across the country, teacher-librarians are losing their jobs or being reassigned. Collections are becoming depleted owing to budget cuts. Some principals believe that in the age of the Internet and the classroom workstation, the school library is an artifact” (9). Within this context, school librarians are looking to our research literature for evidence of the impact that school library programs have on learning outcomes and student success. They are integrating that evidence into their practice, and reflecting upon what can be improved locally. They are focusing on students and showing the impact of school libraries and librarians on student achievement. Todd notes, “If we do not show value, we will not have a future. Evidence-based practice is not about the survival of school librarians, it’s about the survival of our students” (40). In this issue we feature school libraries and their connection to evidence based practice. Former Editor-in-Chief, Lindsay Glynn, began putting the wheels in motion for this feature almost a year ago. She invited Carol Gordon and Ross Todd to act as guest editors of the section, drawing upon their contacts and previous work in this field. The result is an issue with five feature articles exploring different aspects of the connection between school libraries and evidence based practice, from the theoretical to the practical. In addition, there is a thought-provoking Commentary by David Loertscher, asking whether we need the evolutionary model of evidence based practice, or something more revolutionary!In addition to the Feature section, we have a well-rounded issue with articles on the topics of library human resources, and the development of a scholars’ portal. As well, there are a record 10 evidence summaries and our educational EBL101 column. I hope there is something for everyone in this issue of EBLIP – enjoy, and see you soon in Stockholm!
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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 | 0.009 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.015 | 0.020 |
| Insufficient payload (model declined to judge) | 0.099 | 0.050 |
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".