Highly cited articles in the Information Science and Library Science category in Social Science Citation Index: A bibliometric analysis
Bibliographic record
Abstract
This study aims to identify and analyse the characteristics of highly cited articles published in the Information Science and Library Science category in the Social Science Citation Index. Articles that have been cited at least 100 times since publication up to the end of 2012 were analysed. We identified 501 highly cited articles published between 1956 and 2009 in 37 journals. MIS Quarterly published 26% of all analysed highly cited articles. The most productive researcher published 11 articles. Six bibliometric indicators were used to evaluate source institutions and countries. The 13 most productive institutions were all located in the USA and Canada. Harvard University in the USA was the most productive institution, ranked number one in the total number of highly cited articles, while the University of Maryland in the USA had the highest publication performance of first and corresponding author articles. Researchers from the USA contributed 67% of highly cited articles.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.096 | 0.101 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".