A Bibliometric Analysis of Paradiplomacy Research on The Scopus Database Using the VOSviewer Application
Bibliographic record
Abstract
This article seeks to examine the evolution of studies on paradiplomacy thoroughly. This is crucial due to the substantial advancement of this subject in international relations research. This research employs bibliometric analysis using the VOSviewer tool to examine and visually represent the progression of paradiplomacy research in the Scopus database. Within the Scopus database, a total of 214 documents from the years 1984 to 2023 were found that specifically mentioned paradiplomacy. Canada has the most contributors who discuss paradiplomacy, specifically 34 documents. Most articles on paradiplomacy, specifically 68.0%, focus on the social sciences. Simultaneously, Stéphane Paquin holds the record for the highest number of documents authored, totaling ten. From 1984 to 2023, researchers in the field of paradiplomacy focused on 15 topics. These topics included subnational government, United States, diplomacy, diplomatic relations, cultural paradiplomacy, free trade, European Union, Quebec, decentralization, developing countries, federalism, assemblage theory, foreign relations, foreign policy, and sub-state diplomacy. Regarding the advancement of paradiplomacy research, several factors contribute to its development. These factors include the implementation of decentralization in various countries and the growing recognition among sub-state actors of the benefits they can achieve through paradiplomacy activities. This study concludes that between 1984 and 2023, the research on paradiplomacy primarily examined the interests of sub-state actor entities and their paradiplomacy activities. This is evident in the 15 topics received significant attention from paradiplomacy researchers during this period.
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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 | 0.013 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.262 | 0.274 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".