Bibliographic record
Abstract
I often find attending conferences or workshops a source of reflection or inspiration for editorials, and today I attended an event that proved to be no exception. The HEALER network is a UK grouping of professionals interested in health library research. It brings together those working in health information at an academic, practitioner or strategic capacity as well as those working in higher education, research and the NHS. (http://www.libraryservices.nhs.uk/healer/minutes.html)There were a number of interesting presentations, but one (and the subsequent interactive discussions) left me with some worrying thoughts. Hannah Spring (2013) presented some of the findings from her PhD that found when health librarians were asked about their barriers to research they reported that they didn't know what research questions to ask! Alternatively if they had research questions they didn't think to engage with the literature or believed that there was no evidence to answer them! If we really don't have any research questions, and we really don't think to look at the literature or there really is no evidence, this is worrying indeed for the future of EBLIP. It's also a situation I don't recognize from being involved in the EBLIP journal and was left wondering whether it was the health librarians perceptions of “research” and “evidence” that was the issue; questions which are being examined in the LIRG Scan which was described in another presentation. The scan is a review of the evidence on: What practitioners understand by research; what kind of research is relevant to LIS practitioners? How do they use research and what are the barriers and facilitators to using research in practice? (https://sites.google.com/site/lirgweb/home/awards/lirg-scan-award) The results will be used to help inform the Chartered Institute for Library and Information Professionals’ policy on research.The barrier which I’m much more familiar in terms of engaging with research or evidence, is that of accessing the literature. Our strap line says "EBLIP is an Open Access, peer reviewed journal which provides a forum for librarians and other information professionals to discover research that may contribute to 2decision making in professional practice. This is an ethos of which we are proud because we aim to overcome the barriers to making research accessible. For EBLIP, as a journal that strives to make LIS research accessible to the practitioner, open access is the only way forward.I'm pleased to say that this issue is full of both research and evidence, and I hope it will answer some of the questions that arise from your practice, or at least go some way towards doing so. I'm particularly pleased that we have a Feature section on Assessment that comprises articles from the 2010 Library Assessment conference which took place in Baltimore, Maryland, USA. The articles have been peer reviewed at abstract level for acceptance to the conference but appear here as “conference papers”. We are happy to provide an open access forum to this conference material, and welcome the addition of the assessment agenda to the EBLIP journal.Assessment in libraries is an area which isn't always labeled research or evidence based practice but nevertheless provides a wealth of evidence and helps answer questions and demonstrate the impact and value of our library services. These are areas that are crucial to and synonymous with evidence based practice. At our HEALER day, demonstrating value and impact were discussed as areas of research interest that may not always be seen as research by librarians. Demonstrating value and impact is a recurring theme within this issue as we also have a conventional article that was presented at the 2012 Assessment conference (Griffin et al, 2013) as well as Carol Tenopir’s’ commentary on measuring value based on a Keynote address at the DREaM conference that was held in the UK in July 2012.From this issue onwards there are a number of changes within our editorial team. Wayne Jones has left to take up new interests and I would like to thank Denise Koufogiannakis for covering in the interim period. Lorie Kloda is moving to Associate Editor (Articles) and she will be joined by Derek Rodriguez from University of North Carolina, Chapel Hill as a second Associate Editor (Articles) to help with our increasing workload. Heather Pretty is moving to Associate Editor (Evidence Summaries) and Michelle Dunaway is our new Production Editor. We have a new Editorial Intern, Archana Deshmukh from the University of Brighton and Richard Hayman will be our new lead Copy Editor.Finally if you are going to be attending EBLIP7 in Saskatoon in July, I look forward to meeting you there and providing further updates about the EBLIP journal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.065 | 0.395 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.023 | 0.014 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.018 | 0.020 |
| Insufficient payload (model declined to judge) | 0.060 | 0.037 |
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".