Bibliographic record
Abstract
Duplex Stuart Barnes (bio) Nothing of him that doth fade,But doth suffer a sea-changeInto something rich and strange. –The Tempest, 1.2.393–95 My rapist's name was Hebrew: Lion of God.He told me I laughed like his missing uncles. I miss the rolling laughter of uncles who acted marvellously in The Tempest. Cyclone Marcia too was a five-act tempest.I charted the shaking, the aerial earth. In Shakespeare's Ariel's chart there's no earth. My rapist was born under Capricorn. I wonder at the Tropic of Capricorn.I sea-swim, I see the sea change in spring. I sea-swim, I see the sea change in spring. I ring an interstate detective. I state to an interviewing detective:'My rapist's name was Hebrew: Lion of God.' [End Page 253] Stuart Barnes Stuart Barnes is the author of two poetry collections: Like to the Lark (Upswell Publishing, 2023) and Glasshouses (University of Queensland Press, 2016). Glasshouses was awarded the Arts Queensland Thomas Shapcott Prize, commended for the Anne Elder Award, and shortlisted for the Mary Gilmore Award. His writing appears in The Anthology of Australian Prose Poetry, POETRY (Chicago), and Poetry Wales and has been nominated for the Pushcart Prize and shortlisted for the ACU Prize for Poetry, the Montreal International Poetry Prize and the Newcastle Poetry Prize. Recently he guest-edited, with Claire Gaskin, Australian Poetry Journal 11.1, "local, attention." Twitter/Instagram: @StuartABarnes. Copyright © 2022 Wayne State University Press
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.762 | 0.652 |
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".