Mourning and melancholia: An analysis of the Mothers of the Plaza De Mayo
Bibliographic record
Abstract
This paper links the notion of melancholia as endless mourning with the political actions of the Mothers of the Plaza De Mayo, a human rights group in Argentina. These mothers, grandmothers and other protestors refused to accept the death of their children and family members who were taken by the government and disappeared without a trace. The victims were known as “the missing” or “desaparecidos” (“the disappeared”). The Mothers refused to accept that they were dead, thus entering a state of melancholia and endless mourning. This refusal of death is a powerful notion and one that was used politically to protest against the state sponsored violence of the Junta regime in Argentina. This paper first explores the history of Argentina, looking at how that state and military turned on its own citizens in an act of violence and state sponsored terrorism. Second, this paper looks at how mourning functions in a society and what melancholia is by looking at Freudian interpretations. The paper concludes with a discussion of Jean Améry and how important it is not to forget what someone has endured or to be forced to forgive against their will. This leads into a discussion of the signifi-cance of mourning in our society, and how important it is to honour victims of state sponsored violence, whose lives were unjustly taken by the state that was meant to protect them.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".