Australian Academic Librarians’ Experience of Evidence Based Practice Involves Empowering, Intuiting, Affirming, Connecting, Noticing, and Impacting
Bibliographic record
Abstract
A Review of: Miller, F., Partridge, H., Bruce, C., Yates, C., & Howlett, A. (2017). How academic librarians experience evidence-based practice: A grounded theory model. Library & Information Science Research, 39(2), 124-130. http://dx.doi.org/10.1016/j.lisr.2017.04.003 Abstract Objective – To explore and enhance the understanding of how Australian library and information science (LIS) practitioners experience or understand evidence based practice (EBP) within the context of their day-to-day professional work. Design – Constructivist grounded theory methodology. Setting – University libraries in Queensland, Australia. Subjects – 13 academic librarians. Methods – Researchers contacted academic librarians by email and invited each participant to take part in a 30-60 minute, semi-structured interview. They designed interview questions to allow participants to explain their process and experience of EBP. Main results – This study identified six categories of experience of EBP using a constructivist grounded theory analysis process. The categories are: Empowering; Intuiting; Affirming; Connecting; Noticing; and Impacting. Briefly, empowering includes being empowered, or empowering clients, colleagues, and institutions through improved practice or performance. Intuiting includes being intuitive, or using one’s own intuition, wisdom, and understanding, of colleagues and clients’ behaviours to solve problems and redesign services. Affirming includes being affirmed through sharing feedback and using affirmation to strengthen support for action. Connecting includes being connected, and building connections, with clients, colleagues, and institutions. Noticing includes being actively aware of, observing, and reflecting on clients, colleagues, and literature within and outside of one’s own university, and noticing patterns in data to inform decision-making. Impacting includes being impactful, or having a visible impact, on clients, colleagues, and institutions. Together, these categories represent a model that explains the nature of academic librarians’ experiences of EBP. The theory describes academic librarians' experiences as complex and highly contextualized phenomena. There is no clear relationship between these categories, as data analysis did not generate a specific hierarchy of categories. Conclusion – Based on the research findings the authors hypothesize that their study is one of a growing number of studies that has begun to establish an empirical basis for EBP in the LIS profession.
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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 | 0.026 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.004 |
| 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".