Connecting Research and Practice: Publication Patterns of LIS Faculty Who Teach Health-Related Courses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bibliometrics studies of library and information science (LIS) faculty scholarly output have explored publication patterns in open access (Grandbois & Beheshti, 2014), health-gender and sexual orientation (Mehra & Tidwell, 2014), and other trends in LIS Research (Wusu & Lazarus, 2018). This study builds upon that literature by exploring the publication characteristics of full-time LIS faculty teaching health courses and the scholarship patterns of this underexplored group. This bibliometric analysis examined the connections between research and practice by examining publications from 2011 to 2021 by LIS faculty that teach health-related courses for library science programs in the United States and Canada. The data sources were located through searching course listings, faculty profiles, and syllabi from school websites and contacting deans and directors to identify full-time LIS faculty teaching health-related courses in American Library Association (ALA) accredited programs. The 29 LIS faculty that were identified through this process were contacted via email in September 2021, inviting them to voluntarily share their curriculum vitae (CVs) for analysis. The final sample of 21 CVs is comprised of the 16 faculty members who responded to the email invitation providing their CVs and five CVs that were publicly available online. The research team used descriptive bibliometrics to explore author, author order, year of publication, source, type of publication, etc. Insight and implications pertaining to connecting LIS faculty research, teaching health-related courses, and practice will be presented, as well as recommendations for future research directions.
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.
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it