‘Monument to the international community, from the grateful citizens of Sarajevo’: Dark humour as counter-memory in post-conflict Bosnia-Herzegovina
Bibliographic record
Abstract
The challenges of remembering and memorializing the violence of Bosnia-Herzegovina’s tumultuous 20th century have captivated numerous scholars’ imaginations, because Bosnia is a remarkable example of both the utility and abuse of wartime memory. However, the elephant in the room during these discussions is the role of dark humour in narratives of Bosnia’s recent past. This article argues that dark humour is an especially subversive form of counter-memory, that allows Bosnians to express dissent from dominant narratives of the Bosnian War that they perceive as unproductive or divisive. Examples are drawn from oral histories, film and monuments to demonstrate how humour speaks to three major themes of Bosnian remembering: the idea of Bosnians as powerless victims; the seemingly arbitrary nature of the war and its aftermath; and the failures of the international community before, during and after the war. Bosnian dark humour critiques not only the above themes, but simultaneously the social structures in place for discussing the past.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.022 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".