“Institutionalized States of Information Abstinence”
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
In this study, I provide applied examples of using cut-up poetic inquiry as an arts-based research method for analyzing erasure poetry. The erasure poetry was composed by five poet-participants and me during a sensory ethnography that explored embodied experiences of a sexual educator training program. I first overview erasure poetics in the context of sexuality education. I explain how erasure poetry as method can interrupt authoritative proclamations of truth, while also providing a technique to grapple with complex, corporeal data – central topics in sex education research. I then theorize cut-up poetic inquiry as an additional form of erasure, asking and illustrating how the processes of cut-up can distill information to enable emergent analytic insights in the context of my research. Throughout, I meditate on how erasure poetry as an arts- based research method can contribute to discussions of language, discourse, and embodiment in sex education research.
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.
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 | 0.003 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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