“People want good graffiti”: Tensions, contradictions, and everyday politics surrounding graffiti in Hanoi, Vietnam
Bibliographic record
Abstract
Abstract Graffiti has become an omnipresent feature of urban landscapes, with sprawling words and images on public and private surfaces triggering heated debates on the meaning, implications, and legality of these urban inscriptions. Yet, to date, there has been little academic research conducted on graffiti and street art in the Asian context, and none that we could find on the burgeoning scene in Vietnam. In the context of a socialist state, with little tolerance for public dissent, we investigate how, and by whom, graffiti is created, and to what degree it transgresses public space norms in the country’s capital city, Hanoi. We analyse how young graffiti writers negotiate the social, physical, and cultural boundaries which serve as either deterrents or catalysts for graffiti creation, and consider whether strategies of compliance or everyday resistance are employed in order to create their work. With the effects that globalisation and urbanisation have had on the Asian region, and the tactics citizens employ to negotiate state‐imposed censorship and restraints having been studied closely, we position our work within these broader debates.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".