Developing Countries Lag Behind the US and UK in Contributing to Institutional Repository Literature
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
A Review of:
 Bhardwaj, R. K. (2014). Institutional repository literature: A bibliometric analysis. Science &Technology Libraries, 33(2), 185-202. http://dx.doi.org/10.1080/0194262X.2014.906018 
 
 Abstract
 
 Objective – Quantify the IR literature across the world by identifying countries with relatively high concentration of articles, describing the distribution of the literature by language, author (institutional and individual), journal, and examining characteristics such as the transformative activity index, and authorship and citation patterns.
 
 Design – This exploratory study of the literature used several bibliometric research methods to describe patterns and identify highly represented articles, authors, institutions, and journals.
 
 Setting – The Library and Information Science Abstracts database. 
 
 Subjects – 436 articles from 118 journals. 
 
 Methods – Research articles and review papers published through December 31, 2012, were identified by searching Library and Information Science Abstracts (LISA). Citation data for the 436 articles selected was gathered from LISA and Scopus. 
 
 Main Results – The 436 articles from 118 journals had publication dates from 2001 through 2012, originated from 68 countries in 19 languages, and had authors affiliated with 159 institutions. The greatest number of institutional repository articles were published in 2011 while year-to-year growth was greatest from 2005-2006. Most highly represented were the United States and the United Kingdom, followed by India, Australia, and Spain. 
 
 Twenty publishers were responsible for nearly half of the selected articles. The top four journals included OCLC Systems & Services, D-Lib Magazine, Serials Review, and Library Hi Tech. D-Lib Magazine alone published seven of the top 20 most cited articles. While most articles were written by a single author, the majority of the multiple author articles came from developed countries. Citation analysis reveals that the 436 articles were cited 2,071 times, for an average of 4.8 citations per article. However, 147 articles received no citations. The five most prolific authors were Elizabeth Yakel, Kim Jihyun, Karen Markey, Jingfeng Xia, and Sarika Sawant.
 
 Conclusion – The author concludes that developing countries lag behind in establishing and publishing on institutional repositories and suggests that more authors will deposit in IR in the future. A proposed role for LIS professionals is to communicate the objectives, values, and principles behind institutional repositories.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,100 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle