The Impact of Digital Cultural Diplomacy on Security and Global Affairs: the UAE as a Case study
Bibliographic record
Abstract
The concept of digital cultural diplomacy is an evolved form of public diplomacy and a manifestation of soft power. Under the canopy of cultural diplomacy various activities are performed, including diverse art exhibitions, student exchange programs and scholarships, language trainings, museum exchanges and cooperation, culinary and folklore events. In the digital era, cultural diplomacy has been heightening, and soft power is extremely important. Digital cultural diplomacy allows any country to place itself in the global arena with a certain branding, which in turn helps the country achieve its foreign policy goals. The use of social media, and internet in general, has proven to be the most important factor regarding the influence of the target audience. Digital cultural diplomacy is used to strengthen diplomatic relations and build alliances. It allows for greater access to knowledge and information and uses effective means of communication among individuals and organizations. The use of digital cultural diplomacy can reduce financial costs and thus achieve the same goals in a much more efficient way. The necessity of digital cultural diplomacy was fully grasped during the Covid-19 pandemic, where lockdowns made face-to-face encounters and physical exchange impossible. Cultural digital diplomacy has been particularly effective in the UAE. The core values of peace, cooperation and tolerance have been portrayed via digital diplomacy but there is still room for improvement. In this paper seeks to examine the prospects and benefits but also the risks and limitations of cultural digital diplomacy and to provide concrete policy recommendations for the UAE and also other countries in the region that might wish to emulate the example of the UAE.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 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".