Journal of Education for Library and Information Science (JELIS) Through Bibliometric Lenses
Bibliographic record
Abstract
Abstract Purpose: This study aims to examine the published data from the journal of Education for Library and Information Science (JELIS). A quarterly journal of the Association for Library and Information Science Education (ALISE). The study's goal is to provide a venue for exchanging ideas and research in the library field. Designed/methodology/approach: The Journal of Education for Library and Information Science (JELIS) published work between 2015 and 2021 is analyzed using a bibliometric technique. The Authorship Pattern is part of the analysis. Contributions from various organizations and the most dynamic authorship and geographic distribution of the published work. Research limitation(s): The research was limited to five years of performance from 2015 to 2021, and no other factors were considered for this paper. Key finding(s): During 2015-21, a total of 445 Authors contributed 230 papers, averaging 5.2 articles per issue. According to the study, single authors authored 131 (57 percent) of the 230 publications, and the most prolific authors were from the United States of America. Practical implication(s): According to this study, the current style and publication procedures have gaps and loopholes. The analysis will surely raise awareness among potential authors, readers, and library information professionals in general and Journal of Education for Library and Information Science (JELIS) stakeholders and scholars. This research will aid in determining the journal's scope and coverage. Contribution to knowledge: The present research will further highlight the scope of JELIS and contribute a handsome knowledge for the scholars in Canada and abroad. Stakeholders of the Association for Library and Information Science Education (ALISE) and editors of this journal will boost their quality by reading this article. This contribution is the first attempt on JELIS and no other paper relevant to bibliometric on this journal has been contributed by others. This will also help novice researchers who want to research bibliometric examination of various journals and scholarly databases. It will add a scholarly realm by assisting and expanding knowledge’s boundaries.
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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 | 0.021 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.073 | 0.095 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.025 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".