Bibliographic record
Abstract
“Keeping the memory of past events would contribute to a better knowledge of hazards and to the prediction of future events. » (Reghezza-Zitt, Benitez & Devès, 2020, p. 1) Remembering is undoubtedly the best of mentors. But forgetting would also be a precious ally in the perpetual and daily struggle that is life. Indeed, “it is essential that the brain forgets the unimportant details to focus on what really matters, in our daily decision-making.” (Richards & Frankland, 2017, p. 1083) What if we remembered to better accept the tragedy? What if writing helped us to understand it better? What if the words saved us from death? In his play Mother, the third installment in the "Domestics" cycle, an essentially autobiographical work, Wajdi Mouawad, Lebanese-Canadian playwright and director, looks back on his family's exile in the middle of the Lebanese civil war in 1978. Through this work, where the writer plays his own role, the memory of the past is very present, a memory of the still bleeding wound. Mouawad remembers to exorcise the demons that keep haunting him. In what way is writing (and representing) the memory of the tragedy a work of memory necessary to forget to let oneself die? We will first consider the mechanisms of memory and forgetting, before turning, in a second part, to the role of theater in the process of remembering, catharsis and overcoming.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".