Academic Librarian Competency: A Description of Trends in the Peer-Reviewed Journal Literature of 2001-2005
Bibliographic record
Abstract
Decribes publishing trends in academic librarian competency articles to provide context for a later investigation of definitions found in this library and information science (LIS) literature. Explores peer-reviewed articles from 2001 – 2005 to determine: who is writing on academic librarian competency, including any collaboration; whether there are areas of focus in the literature; if these articles are published in academic journals and to what degree; whether we incorporate other literatures, especially those relevant to competency; and what other trends may be important to an understanding of this topic. Discovers three major areas of focus: management-related with 35 articles, 19 education and professional development articles and 12 articles on professional issues. Most are written by single authors and by authors associated with academic libraries or library schools. There are only three college-based articles. There is minimal collaboration across boundaries of any kind. Most of the authors associated with academic libraries are writing the management-related articles. The majority of these authors are US-based. The majority of articles on education and continuing professional development are written by authors at library schools. Further, these authors represent a more international representation of this topic and a greater degree of international collaboration than found in the management articles. The authors who wrote articles on professional issues are almost equally from library schools and libraries.
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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.058 | 0.068 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".