Material Weapons: Paratext, Ethics, and Testimony in Carmen Aguirre’s Something Fierce
Bibliographic record
Abstract
From its title onward, Something Fierce uses a host of material strategies that position the book as a testimonio – narrating Carmen Aguirre’s Memoirs of a Revolutionary Daughter not only as a coming-of-age memoir, but rather as the communal story of the Chilean resistance, expressing an urgent justice claim, and invoking readers’ responsibilities as witnesses. To develop my analysis of Something Fierce, I consult scholarship on paratext, the genre of testimonio, and research on the ethical and political stakes of testimonies as cultural commodities. I thus establish the key role of paratext as strategic “thresholds of interpretation” (Genette) that allow renegotiating the dynamics of the memoir’s national and transnational “testimonial transactions” (Whitlock). In so doing, I demonstrate how the material envelope of Something Fierce serves to mobilize testimony’s call-and-response dynamics, to revise the power-balance between the testifying subject and their addressees – asserting authorial agency and invoking audience’s implication.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".