Bibliographic record
Abstract
In this article, which includes a feminist micro-chapbook, the author has chosen poems written both prior to and following their recollection of and subsequent therapeutic struggle to work through their lifelong experiences of sexual harassment and assault. Situated within the neoliberally co-opted #MeToo campaign, Betsy Devos’s 2020 Title IX cross-examination mandate, and post-Trumpian, ongoing COVID U.S. landscape, this work performs an ethnographic autopsy on the body politic: displaying the fleshy lived consequences of an unjust legal system. By continuing Faulkner’s work on poetic inquiry as feminist methodology, this piece contributes to the tradition of poetic praxis as a means of clapping back to structures of oppression. At its core, this article reveals relived experiences and words spoken by institutional figures reluctant to fulfill mandatory reporting requirements. By playing off Higginbotham’s (1993) term respectability politics, “Requirement Politics” blurs lines of academic and poetic writing to deliberately collapse a fabricated line between public and private lived experiences.
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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".