Bibliographic record
Abstract
After 14 complex years, I message him: “I keep saving you and losing me.” M hangs himself. Numbly I sit holding M’s cold dead hand in my warm shaking one. I’m 33. A widow. Twenty years on, and now a creative arts therapist/educator/researcher, I launched an arts-based autoethnographic (abr+a) quest to exhume and frankly face my role within my husband’s suicide. Naively, I imagined cultivating an ecotone where self-care and care-for-other intra-act. Lured by this poietic methodological experiment, Scarcity-Gargoyle, however, sloped in— an inner-alter symbolising a trauma-response that had outlived its usefulness. Leading a motley crew of author, animangels, Darwin, and new material/posthumanists, it incited a gyroscopically-circling contemplation of trauma and scarcity, now folded into this Exquisite Corpse game. As this game unfurls, the question lingers within creases and crevices: What might these critters speak/sing/growl/howl/whisper/rasp to the lofty aspiration of crafting capacity for simultaneous compassionate becoming-with self and other?
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 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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".