Wanting to Call this Poem Clerestory, I Settle on Collateral Damage, and: Late April, and: Shinrin-Yoku, January
Bibliographic record
Abstract
Wanting to Call this Poem Clerestory, I Settle on Collateral Damage, and: Late April, and: Shinrin-Yoku, January Erin Wilson (bio) Wanting to Call this Poem Clerestory, I Settle on Collateral Damage I would ratherbe alonein the white lightof a stone churchthan under this hostileretail lighting as the birdlike bonesin my handsfinally breakand the tinyhammersin my earsgrow still but someonemust paythe governmentsfor their wars. [End Page 165] Late April I take my shrunken wool sweater off,the one I know affectionately as my Marina Tsvetaeva sweater(the camel-colored one with the holes whose buttons hangfrom silver shanks like little sleepyheads). I peel, wash, and salt raw turnipand bite a hunk off. I put Chopin's "Preludes" on the record playerand force a window open. A young girl in my neighbor's yardkneels with bare legs in a cool-green grass of fire. [End Page 166] Shinrin-Yoku, January Green wind, white pine do not buywhat they're selling! Green wind, white pine (breath) black thoughtsget filtered out Green wind, white pine fists loosenwelcome the palms again Green wind, white pine eyes turn inwardwhere snow begins to fall [End Page 167] Erin Wilson erin wilson's poems have recently appeared in Vallum Magazine, Tar River Poetry, The Shore, Verse Daily, and Valparaiso Poetry Review. Her first collection is At Home with Disquiet; her second, Blue, is about depression, grief and the transformative power of art. She lives in a small town on Robinson-Huron Treaty Territory in Northern Ontario, Canada, the traditional lands of the Anishnawbek. Copyright © 2023 University of North Dakota
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.365 | 0.225 |
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".