Modeling Digital Paradiplomacy in the Global Space. A Strategy for Neutralizing Information Threats
Bibliographic record
Abstract
The article explores the phenomenon of digital paradiplomacy as an innovative instrument for countering information threats in global space. The relevance of the topic stems from the growing role of disinformation campaigns in international politics, carried out by both state and non-state actors with the aim of undermining democratic institutions, damaging state reputations, and destabilizing local communities. The purpose of the study is to define the role of digital paradiplomacy in transforming contemporary international communication and to develop an algorithmic approach for its application in addressing global disinformation challenges, particularly in the activities of subnational actors. The article examines the transformation of diplomatic practices in the context of the digital age, as well as the theoretical foundations of paradiplomacy and its evolution from a supplementary component to a strategically significant component of international communication. It analyzes how subnational entities use digital platforms to shape narratives, engage with international audiences, counter disinformation, and mobilize support. A five-stage algorithm for digital paradiplomacy is proposed. The article presents examples of digital strategy implementation in countries such as Estonia, Lithuania, Ukraine, the United States, and Canada, demonstrating successful practices of integrating local initiatives into national and international digital security systems. Particular attention is given to the potential for municipalities to cooperate with diasporas, non-governmental organizations, and tech companies to amplify the international reach of their messages. The importance of digital literacy, ethical content, and institutional cooperation is emphasized as the foundational conditions for effective digital paradiplomacy. The conclusion argues that digital paradiplomacy is not only a crisis response tool but also a mechanism of strategic communication capable of strengthening democratic resilience, reputational subjectivity, and the informational autonomy of regions in the digital age. Future research should focus on quantitatively assessing the effectiveness of such strategies, developing adaptive local-level response tools, and deepening interdisciplinary analysis of the intersection between paradiplomacy, information security, and digital communications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".