Bibliographic record
Abstract
This article investigates the vicissitudes of the term “femicide” in order to draw out its nuances, elisions, and assumptions to understand its political reach as well as its limits. Ultimately, my aim is to argue that “femicide” cannot sufficiently account for the violence meted out against black women, whose non-positionality, structural violability and availability to all serves as libidinal and political currency in the conceptual elaboration of “sexual violence.” The explanatory power of the term “femicide,” presumed to have a global application, lies in its analogizing of women’s experience by way of shared biological attributes to articulate their structural vulnerability in relation to males qua bearers of the phallus, within a heteronormative paradigm of sexual desire and object choice. If, as I contend, an antiblack erotics animates the figuration of “woman” as she functions in the disciplinary field of anthropology and in the discourse generalizable as feminism, this article is necessarily an examination of the predicament of attending to sexual violence under conditions of racial capitalist modernity. At stake, more broadly, then, is how these predicaments might also inflect the critical lexicon of feminist discourses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.069 | 0.013 |
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".