Identifying Key References and International Trends in Transparency: A Scientometric Analysis of Scientific Productions over the Last Decade
Notice bibliographique
Résumé
Objective Transparency is an interdisciplinary concept that has emerged in multiple management fields such as governance, economy, health, law, media and even religious institutions. Examining the structure of knowledge, developments and current trends in the field of transparency indicates the change of informational approaches (focused on accessibility and disclosure of information) to emerging social approaches. The aim of this study is to identify key references and international trends of the transparency phenomenon at the international level. Accordingly, trends in publication and citation, main actors at the country and organizational levels, leading media outlets including publishers and journals, and established and emerging research fronts based on topics and key terms in the field of transparency have been identified. Methods To extract related scientific productions, the Web of Science Core Collection was utilized, encompassing databases and citation indexes of social and human sciences in journals, conferences, and books. Queries were formulated based on a combination of Title, Author Keywords, and Keyword Plus, refined by the research area of economics, spanning the years 2013 to 2022. Data processing, analysis, and visualization followed scientometric principles, techniques, and concepts. The Clarivate database was consulted for bibliographic data, content, and citation data of scientific productions, while the JCR database was used for data related to scientific journals. Network and overlay maps for citations, co-occurrence of keywords, and their clustering were conducted using the VOS Viewer software. For co-occurrence calculations, a full counting method was applied with threshold. Results Analyzing 1,163 scientific outputs indexed in the field of transparency revealed a dynamic trend with an average annual growth rate of 9.38% in publications and 40.27% in citations. In the last year, the rate of publications in this field surpassed double the average. The standings of participating countries, based on their production share, the volume, and age of received citations, were evaluated to monitor their competitive behavior. Institutions such as the University of London, National Bureau of Economic Research, University of California, European Central Bank, and Udice French Research Universities emerged as the most active in the transparency domain. In this collection, 30% of the works were published in 5% of the journals, as well as top publishers being introduced. The analysis identified key thematic axes at three levels: Research Areas, Citation Topics Meso, and Citation Topics Micro. The top ten Citation Topics Micro, in order, are: Monetary Policy, Corporate Governance, Economic Growth, Option Pricing, Cooperation, Elections, Public Administration, Health Technology Assessment, Antitrust, and Corporate Social Responsibility. Finally, a total of 145 co-occurring keywords were categorized into five clusters, and the trends of leading countries (USA, UK, Germany, China, France, Netherlands, and Canada) in these concepts were compared. Conclusion Examining the production status of countries, the dynamic rankings of participation in outputs, the volume and age of received citations, and the unique thematic trends of each country, underscores the importance of national planning for success in transparency management. On the scientific development path, identifying key references in transparency paves the way for productive research advancements and interaction with transparency leaders, and familiarity with current trends in this domain facilitates efforts towards promising directions. The composition of the top identified organizations, encompassing academic, non-profit, and supranational entities, suggests that success in the transparency realm necessitates regulatory measures for a balanced growth of academia, market, and industry. The knowledge structure of the transparency field highlights the necessity to consider a broad spectrum of stakeholders, both legal and natural individuals, in roles such as policymakers, business managers, and researchers within the transparency ecosystem. Universal thematic axes and country-specific indigenous axes provide insights for devising research agendas, enabling us to align with global understanding in addressing our top-priority issues.
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Comment cette classification a été obtenuedéplier
Étiquettes directes de modèles (non validées)
Étiquettes de catégorie et de devis d'étude par modèle, issues des rondes d'étiquetage. C'est une sortie machine, non validée, et le désaccord entre modèles est livré comme donnée. Aucun devis ici n'est encore validé contre MEDLINE.
| Bras | Catégories | Devis d'étude | Confiance |
|---|---|---|---|
| gemma | Bibliométrie Domaine: non disponible · Genre: Empirique Porte sur le système de recherche canadien: non · Porte sur un sujet canadien: non | Observationnel | low |
| gpt | Bibliométrie Domaine: non disponible · Genre: Autre Porte sur le système de recherche canadien: non · Porte sur un sujet canadien: non | Observationnel | low |
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,028 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,079 | 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 découleClassification
machine, non validéeÉtiqueté directement par 2 modèles lisant le dossier complet.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».