“Your wall cannot divide us”: Graffiti in Cyprus and insights into conflict-affected landscapes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Graffiti in conflict-affected settings offers alternative understandings of local experiences and international challenges that intertwine with everyday routines and spaces. Urban walls deliver canvases to write, tag, and paint to express grievances and aspirations for more peaceful futures, illuminate societal concerns, and offer solidarity on issues that sit within and outside the confines of historical and present-day division. In this expanded visual essay, we explore the publicly available resource of graffiti to gain insights into the challenges and priorities of Cyprus’ conflict-affected landscape. Drawing on observations on both Greek-Cypriot and Turkish-Cypriot sides of the United Nations Buffer Zone, we explore the ways in which graffiti provides space to recognise alternative voices in a society where official and media discourses remain characterised by language of difference and political division. Insights gained through walking surveys conducted in June 2019 were augmented by discussions with local experts to further contextualise the observed graffiti content. We demonstrate the potential value for academics, policymakers, and practitioners of analysing the languages, symbols, and messages of graffiti. We conclude that this initial exploration establishes graffiti as more than ‘vandalism’ and expands our knowledge of conflict-affected landscapes as an indicator of the everyday and the interactions, priorities, and spatial politics of local people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 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 it