Bibliographic record
Abstract
Other| November 01 2022 The Pigeon King Ace Clamber Ace Clamber Ace Clamber is a Calgary-based writer whose work explores the intimate day-to-day moments of growing into and navigating adulthood as a trans man. He is fascinated by the everyday, the things everyone can all relate to. He is hopeful that by telling these stories, he can help shape the kinds of trans stories that are told, pushing beyond narratives that center trauma and violence. He was a participant of the Banff Centre for Arts and Creativity Fall 2021 Writers Residency. His first film project, Scaring Women at Night, was an official selection of the 2022 Toronto International Film Festival’s (TIFF) Short Cuts program. Search for other works by this author on: This Site Google the minnesota review (2022) 2022 (99): 33–37. https://doi.org/10.1215/00265667-9992999 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Ace Clamber; The Pigeon King. the minnesota review 1 November 2022; 2022 (99): 33–37. doi: https://doi.org/10.1215/00265667-9992999 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search Books & JournalsAll Journalsthe minnesota review Search Advanced Search The text of this article is only available as a PDF. Copyright © 2022 Ace Clamber2022 Article PDF first page preview Close Modal Issue Section: Creative You do not currently have access to this content.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.258 | 0.108 |
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".