# <i>SpendYourSummerInGeorgia</i> : popular geopolitics, grassroots activism and tourism marketing against Russia
Bibliographic record
Abstract
This article demonstrates the broad-spanning ramifications of tourism marketing in geopolitics and proposes viewing civilian-led social media destination branding campaigns as novel yet important forms of popular geopolitics. The case is the #SpendYourSummerInGeorgia campaign created by Georgian grassroots activists in 2019 following a politicized travel blockade issued by the Kremlin preventing Russians from entering Georgia. #SpendYourSummerInGeorgia was designed to counter the blockade, soliciting an alternative, pro-Western and European tourism audience. It enabled citizens to engage in their country’s foreign relations – a space historically reserved for political elites – yet one now accessed through tourism marketing. This campaign also shaped representations of Georgian collective identity, including those linked to Europe and the Soviet Union, thus ordering social, cultural and political values in the country. Contributing to literature across popular geopolitics, tourism geographies and nation branding, this article uses content analysis and semi-structured interviews to show how tourism was not only impacted by geopolitics but also became its very medium. As popular tourism marketing enters the messy world of geopolitics, this case demonstrates how the stakes for cultivating a strategically favourable collective identity are high, calling for those studying popular geopolitics to have their radar attuned to tourism.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".