Bibliographic record
Abstract
Since the Guatemalan genocide against Maya populations (1981-1983), domestic and international human rights groups have organized truth commissions, forensic exhumations, and legal cases. These efforts to secure justice have achieved minimal success, prompting a reconsideration of the relationship among narrative testimony, visual testimony, and institutional standards of truth. Engaging the ideas of visual studies scholar, Nicholas Mirzoeff, I argue for the political importance of testimony that is critical of such standards, including those enforced by human rights’ legal paradigm. Following Mirzoeff’s understandings of “visuality” and “countervisuality,” I analyze “visual testimony” as that which acknowledges the dynamic interplay between word and image, as well as various power relations. More specifically, I explore how genocide survivor Rigoberta Menchú and performance artist Regina José Galindo employ this type of testimony to express rage, which I associate with witnesses’ right to testify on their own terms, beyond institutional processes and imperatives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".