Bibliographic record
Abstract
Mark Yourself for the Dead Constant Laval Williams (bio) The needle pierces my flesh again,another one lost, 3,000 maims a minute.When I die, the ink in my body will breakdown like a levee—rising at the wallsof my skin, a clock-smelted alphabet,a dark code—until one tiny fractionof cell gives way, a microscopic fissure,and all these old ghosts are releasedin a gust of dusk—the one who felloff the cliff when we were eighteen,the one who overdosed on fentanyl,my dad playing his piano, plunking out"Hymn to Freedom" as we all shiversmaller and smaller, join the whirlingwheel of ether we fought againstfor such a very long time. [End Page 153] Constant Laval Williams Constant Laval Williams is from Los Angeles, California. He studied creative writing at the University of Southern California, where he received the Beau J. Boudreaux Poetry Award. He is currently pursuing an mfa at the Iowa Writers' Workshop. His poetry has appeared in Sugar House Review, Painted Bride Quarterly, and Bellevue Literary Review, among other publications. Copyright © 2022 University of Nebraska 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.116 | 0.074 |
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".