What Do Australian Library and Information Professionals Experience as Evidence?
Bibliographic record
Abstract
Abstract Objective – This article presents the findings of a project which established an empirical basis for evidence based library and information practice (EBLIP). More specifically, the paper explores what library and information professionals experienced as evidence in the context of their professional practice. Methods – The project consisted of two sub-studies. The public library sub-study was conducted using ethnography. Over a 5-month period, a member of the research team travelled to a regional public library on 15 occasions, staying between 3 and 4 days on each visit. The researcher observed, interacted, and became involved in the day-to-day activities of this library. These activities were recorded in a journal and added to the researcher’s insights and thoughts. Additionally, 13 face-to-face interviews with staff in positions ranging from the operational to the executive were conducted. The academic sub-study was conducted using Constructivist Grounded Theory. Semi-structured interviews were conducted either in person or via Skype, with 13 librarians from Australian universities. Interviewees were in a diverse array of roles, from liaison librarian to manager and library director. Results – The project found that the Australian academic librarians and the public librarians who participated in the project experienced six elements as evidence: observation, feedback, professional colleagues, research literature, statistics, and intuition. Each of these will be described and highlighted with examples from each of the two studies. Conclusions – The findings of this study revealed many similarities in the way that library professionals from both studies experienced evidence. Evidence was not hierarchical, with evidence from many sources being valued equally. In contextualizing evidence and applying to the local environment, library professionals were able to draw upon more than one source of evidence and apply their professional knowledge and experiences. In this way evidence was more nuanced.
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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 | 0.033 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".