Studying political decision-making as a cognitive process: is it interdisciplinary? A bibliometric analysis
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
Introduction At the turn of the 21st century, concerns emerged regarding whether research at the intersection of psychology and political science should be regarded as a multidisciplinary subfield within political science or an independent, interdisciplinary field that contributes to both disciplines. More than twenty years later, how does the literature on political decision-making approach this issue? Should this application of political cognition research be viewed as a multidisciplinary subfield within political science, or as an independent interdisciplinary field contributing to both political science and psychology? This study examines the organizational framework of research and the trends in publications within the literature on political decision-making. Methods Through a bibliometric analysis, this study aims to enhance readers’ understanding of the disciplinary characteristics of research in political decision-making. The analysis examines how publications are distributed across various disciplines and among different researchers contributing to the study of political decision-making, as well as the most frequently used methodologies in this field. Results The findings suggest that research tends to be more multidisciplinary than strictly interdisciplinary. This conclusion is based on three observations: (i) most publications are in political science journals; (ii) much of the research is conducted by political scientists; and (iii) the research mainly uses political science frameworks and observational designs despite political scientists’ familiarity with experimental designs. Departmental affiliation is the key factor in predicting cited literature, with political scientists favoring political science research and psychologists leaning towards psychology research. Discussion The results of this study suggest that while political decision-making research draws on expertise from both disciplines, it remains fundamentally anchored in political science. Recommendations include attending conferences outside the researcher’s primary discipline, provided they are relevant to their research agenda. Researchers should explore the various specialized grants and funding opportunities that aim to promote the development of new research questions and testing new methods, theoretical approaches, and innovative ideas. Faculty should integrate various disciplines into the curriculum to offer valuable and broadly applicable knowledge. By promoting open interdisciplinary dialogue, political scientists and psychology researchers can work together more effectively to tackle the challenges of political decision-making research.
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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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,037 | 0,183 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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