LIS Research Productivity According to Gender
Bibliographic record
Abstract
Purpose-The present study aims to explore the publication trend, authorship pattern and research productivity by male and female authors in the field of Library and Information Science research. Design/Methodology/Approach- A total of 571 articles published in selected three LIS Emerald journals viz., i) Library Management, ii) New Library World iii) Performance Measurement and Metrics during 2009-2018 are downloaded from Emerald group of publishing. The data related to the author’s gender, affiliation, university and country are extracted and saved in a separate file for further analysis. Influence of gender was assessed with respect to at individual and collaborative level. The result of the study found that there has been an increase proposition of female authors over the years with a resulting decline in male authors. Findings- The result of the study found that there has been an increase proposition of female authors over the years with a resulting decline in male authors. Furthermore, even as LIS teachers (52.58%), LIS professionals (63.46%) and Research scholars (51.72%), female authors are more productive compare to male authors. Further, it is observed that USA is the most productive country by contributing the highest number of articles (159). Of the 159 articles, 65.13% of articles are authored by female authors. The faculty members from University of Punjab, Pakistan have contributed the highest number of (10) articles and occupied the first place in ranked list of universities. Research limitations/implications: The study examines the authorship pattern and also investigates the gender participation in LIS Research. The findings of the study will help in lying down the real picture and the publication productivity by male and female authors in the field of Library and Information Science. The study recommends that the governments/concerned authorities need to support and motivate women researchers to publish more qualitative articles in reputed journals. Originality/Value- The study is the first of its kind to explore the research productivity by male and female authors in the field of Library and Information Science.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".