Bibliographic record
Abstract
Invocation, and: Fire Starter Alycia Pirmohamed (bio) Invocation Somewhere, they are kneelingand I am forgetting your name, how to hold each fragmentof sound in my mouth— Allah,my thoughts are scattering in the wind. They land in Dar es Salaam,in India, in miles of golden grass.Sometimes, they fall into my own palms as I pray next to my fatherfor my father. My Father, I am discovering howto feel loneliness in a series of languagesby cutting open each word like a dark black plumonly to eat the skin. [End Page 105] Tell me I am a little closerto the beginning that I am a young tree on the sideof a mountain, a birdcircling a volcano, or simply a sound travellingvertical. Fire Starter This is the humof a northern forest. Don't forget all of the saltthat has gone into this healing— winceif you must, call out to India for two hundred yearsif you must. I am building a home andburning down my body that has never feltlike my body, drinking from a springto balance [End Page 107] all of this smoke. I am building a firethat snags onto the redwoods. I want to redesign this dishmy body was born into,cardamom and brown skin multiplying within the agar.Hair that smells like burning grass,a landscape that reaches for another land. [End Page 108] Alycia Pirmohamed Alycia Pirmohamed is a PhD candidate at the University of Edinburgh, where she is studying figurative homelands and the work of second-generation immigrant artists in Canada. Her work has recently appeared or is forthcoming in Glass: A Journal of Poetry, wildness, Dogwood: A Journal of Poetry and Prose, Grain Magazine, and Vallum Contemporary Magazine. She was born in Alberta, Canada, and she received a mfa from the University of Oregon. Copyright © 2018 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.464 | 0.249 |
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".