A Content Analysis of Librarianship Research
Bibliographic record
Abstract
Objective: To conduct a content analysis of library and information studies (LIS) literature published in 2001 and test the domains developed by Crumley and Koufogiannakis. Methods: A comprehensive list of refereed library and information studies journals was compiled and reviewed independently by two researchers to derive a list of included journals. Articles published in 2001 from included journals were independently assessed for relevancy by two researchers. Researchers separately extracted and checked data from included articles. Results: 217 LIS journals were reviewed and 107 were included; 91 journals provided data. 2664 journal articles were examined, with 807 (30.3%) classified as research. The Top 10 journals for research published in 2001 were: 1) JASIST, 2) Scientometrics, 3) Info Proc & Man; 4) Coll & Res Lib, 5) Tie: J Lib Adm/Bull Med Lib Assn, 7) Libs & Culture, 8) J Doc, 9) Tie: J Info Sci/J Acad Libr. For the period studied, descriptive research (329 out of 807 articles) was published far more frequently than any other type. The domain Information Access & Retrieval had the highest number of research articles (314/807), followed by Collections (193/807), Management (135/807), Education (95/807) and Reference (77/807). Two new possible domains were identified: Library History and Professional Issues. Conclusions: Because 36 articles fell into the domain of Professional Issues, a case can be made to add this domain to Crumley and Koufogiannakis’ taxonomy. Library History was not added as a domain because historical research is not used for evidence-based decision-making. There was no evidence to support keeping the Marketing & Promotion domain. LISA provides the best coverage of the top 10 LIS research journals identified in this study.
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 | 0.024 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.052 | 0.045 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| 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".