Tracking Theory Building and Use Trends in Selected LIS Journals: More Research is Needed
Bibliographic record
Abstract
Objective - The authors measure theory incidents occurring in four LIS journals between 1984-2003 in order to examine their number and quality and to analyze them by topic. A third objective, only identified later in the text of the study, was to compare theory development and use between Korean and international journals. Research questions asked include whether LIS has its own theoretical base as a discipline, and what characteristics the theoretical framework has. Design – Bibliometric study. Setting – Journal issues selected from four LIS journals for the time span from 1984 - 2003. Subjects – Two international journals, Journal of the American Society for Information Science and Technology (JASIST) and Library and Information Science Research (LISR) were selected based on their high ranking in the Social Sciences Citation Index (SSCI) impact factors. Two Korean journals, Journal of the Korean Society for Information Management (JKSIM) and Journal of the Korean Society for Library and Information Science (JKSLIS) were selected. Methods - After having determined a definition of theory, and identifying different levels of theory, the authors set up rules for the identification of theory incidents, which are defined as “events in which the author contributed to the development or the use of theory in his/her own paper” (550). Content analysis of 1661 research articles was performed to measure theory incidents according to working definitions. Interrater reliability was ensured by conducting independent coding for “subfield classification, identification of theory incidents, and quality measurement” (555), using a sample of 199 articles (random selection not specified), achieving 94-97% interrater reliability. Incidents, once identified, were evaluated for quality using Dubin’s “efficiency of law” criteria, involving measures of relatedness, directionality, co-variation, rate of change, and “profundity,” defined as the depth to which theory is incorporated into the research study. Main Results - 21.79% (n=362) of the articles contained theory incidents that were analyzed and evaluated. Trend measurement indicated an overall increase, although a slight decrease was shown in the year range 1993-2003. International journals accounted for 61.33% of theory incidents, compared to 38.67% for the Korean journals. T-testing showed that differences in means between Korean and international journals were not statistically significant. Topical theory areas were ranked by frequency. The top five areas were shown to be nearly identical between Korean and international journals. ANOVA was performed with significant results in the difference between efficiency ratings. Conclusion – The authors find that the overall proportion of theory incidents including both theory development and use increased through the 20-year time span examined, and that LIS has established its own theoretical framework based upon the frequency of incidents.
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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 | 0.059 | 0.184 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.021 | 0.034 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".