Bibliographic record
Abstract
Kiwetinohk Ohci Samantha Nock (bio) stop at the edge of everything—bend down and stick your hands in the dirt.grab a fist full of soil and pull it close: inhale. this earth has been heresince before nicâpân setone foot in front of the other. southerners from the city keep calling these lands a wastelandbecause in the south all they can seeis bountiful opportunity everywherebut north of Hope. i come from where frost explodes treeswhere grandpa makes coffee on the campfire,grounds spilling into fried eggs.i come from hunting seasonsand midwinter snow drifts. if you listened to me you would hearthat this place is where the world begins—you can stand at the edge of the bluffand see where muskrat danced. the knowledge i have from surviving northern wintershas helped me in this citybut i would be lying if i said i didn'tdream of whiskeyjacks and grandpa's alarm clockroaring the CBC at 6am. [End Page 203] if one more white environmentalisttells me thatthe north is a lost causei will show hima lost cause if you lay on your back along the sukunkayou can see every starthis is where nipapapointed and said:"that's the north star. if you're ever lostyou can follow her home." [End Page 204] Samantha Nock Samantha Nock is a Cree-Métis writer currently living on the unceded territories of the Musqueam, Squamish, and Tsleil-Waututh peoples. She grew up in Treaty 8 territory in Northeastern BC, but her family originally comes from Ile-a-la-Crosse, SK (Sakitawak). She has published work in Canadian Art, GUTS Magazine, SAD Mag, PRISM international, among others. Her essay, "Saw Your Instagram," featured in the Fall 2018 issue of Canadian Art, was nominated for a National Magazine Award in the Personal Journalism category. Samantha's poem, pahpowin, was the second runner-up in the PRISM International Pacific Spirit Poetry Prize. Copyright © 2020 Johns Hopkins University Press and the University of Calgary
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.802 | 0.485 |
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".