Diamanda Galás and Amanda Todd: Performing Trauma’s Sticky Connections
Bibliographic record
Abstract
Though trauma transgresses borders and produces displacements, too often its study and the treatment of its harmful affects contain it historically, geographically, and institutionally. In the process, trauma becomes dislocated from the larger affective economies through which it is produced. Following the lead of feminist and queer studies scholars, Ann Cvetkovich and Sara Ahmed, Helene brings together two performances—Diamanda Galás’s Defixione , Will and Testament: Orders from the Dead, and Amanda Todd’s My Story: Struggling, bullying, suicide and self harm—to illuminate sticky connections across the geopolitical particularities of violently produced trauma. She proposes that Galás’s and Todd’s performances of two radically disparate traumas—genocide and sexual assault—need to be understood as contemporary variations of traditional laments that use embodied affective expression to communicate the overwhelming and “inarticulate grief” associated with the trauma of loss and violation (Holst-Warhaft Cue 4). With this essay, Vosters aspires not only to bring Galás and Todd into dialogue, but also to join with them as part of an interdisciplinary and polyphonic chorus of lament against the forgetfulness of trauma’s production.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.052 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".