(En)countering dissonance : the semiotics of the living memorial counter-monument in Budapest
Bibliographic record
Abstract
In recent years, several studies have shown an observable shift in the mainstream memory narratives about World War II and the Holocaust in Hungary, mainly – and sometimes exclusively – emphasizing the victimhood of the Hungarian nation during these historical events. In several cases, grassroots action has been taken to bring attention to the dissonance of these narratives. One of the most prominent instances of grassroots activism challenging the state’s official memory narrative is the Living Memorial, installed as a counter-monument to the Memorial of the Victims of the German Occupation of 1944 in Budapest’s Liberty Square. The aim of this study is to analyze the semiotics (imagery and symbolism) of the two memorials, as well as the public response given to their installation. The chapter illustrates how memory narratives and commemoration practices may become instrumentalized in right-wing populist discourses, in which the nation is seen as a central point of reference and a source of social cohesion and pride; therefore, any narratives that would bring ambiguity, shame, or guilt to the nation, are rejected or reframed. The chapter furthermore investigates how counter-commemorative practices may serve to design the social sustainability of dissonant or contested heritage. The notion of counter-monument is discussed as a strategy to challenge hegemonic memory discourses.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".