‘I’ve grown fearful of any rustle behind me’: defining anticipating discriminatory violence <i>as</i> violence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Marginalised people fear and expect violence, often daily. This prompts us to ask, is anticipating violence a violence in and of itself? Asking and answering this question extends the feminist, critical race, violence and trauma studies project of broadening traditional understandings of violence to name ignored forms of violence as violence (e.g. epistemic or representational violence). Ultimately, we argue that anticipating discriminatory violence is violence in and of itself. To do so, first we contest the common assumption that violence is intentional. The idea that violence needs to be intentional is a long-held myth that functions to deny various forms of violence. Second, we challenge the idea that violence requires a clear perpetrator. Systems of oppression and discriminatory ideologies enact violence, but there often is no clear perpetrator. When we are preoccupied with claiming that violence involves an intentional actor, we neglect to attend to the ways in which oppressive ideologies and systems structure marginalised people's daily lives and experiences of (anticipating) violence. Living under the Western capitalist cisheteropatriarchal regime renders the ‘everyday’ a site of trauma and violence. This framework for reconceptualising what ‘counts’ as violence creates space to move beyond violence in its most traditional forms: the punch, the slur. Anticipating violence is the logical consequence of living under systems of oppression. When a group of marginalised people collectively anticipate violence, it is clear violence has already happened and is happening all around us: we posit that our conceptualisation of anticipating violence as violence is not intended to validate all forms of anticipated violence.
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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 | 0.002 | 0.001 |
| 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 | 0.001 | 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 it