Thanatographical fiction: Death, mourning and ritual in contemporary literature and film
Bibliographic record
Abstract
In recent years, many authors around the world have taken on the difficult task of commemorating the unmourned dead caused by wars, terrorism or structural violence, or of giving them a literary burial. Their fictions, which I will call thanatographical fiction in the following, play a central role for the collective imaginary in that they provide an archive of knowledge on how violent death and grief are processed. The study of a comparative corpus shows that there is a transcultural and transmedial poetics of grief that serves to frame and channel emotions, to give them a form that allows access to them without sparking further excess. What I aim to demonstrate is that the common grounds of fictions from such diverse places as France, Québec, Senegal and Ukraine are that they can illustrate processes of the economy of emotions: in order to address the subject of violent death, they have to resort to different strategies of emotion control. By modulating emotions, texts and films influence both the regulation of grief and commemoration on one hand, and on the other, the reinforcement of collective identities. They can thus provide an instrument for reflecting on the interaction of grief and violence to gain a better understanding of it. I will thus analyse Wajdi Mouawad’s tetralogy of plays Le sang des promesses , Mohamed Mbougar Sarr’s novel De purs hommes , Valentyn Vasyanovych’s film Atlantis and Julie Ruocco’s novel Furies to elaborate a first draft of a thanatographical poetics of grief.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".