Bibliographic record
Abstract
The following description is provided by the publisher: CONTENTS THE JACOB ZILBER PRIZE FOR SHORT FICTION JUDGE'S ESSAY Kristen Arnett 7 Reimagining Place THE JACOB ZILBER PRIZE WINNERS Kate Finegan 8 Bears and Other Beasts Joseph Pearson 23 An Iconostasis Susie Taylor 69 Vigil FICTION Paulette Jonguitud 35 Running to Stand Still Laura Clarke 57 Pothos Alisha Dukelow 83 The Jellyfish NON-FICTION Dominik Parisien 45 Open letter to an unknown sibling POETRY Rhiannon Ng 19 [eulogy for roadkill on a Yukon solstice] Kai Conradi 21 After my mom left my dad he took me to the mall Dana Jaye Cadman 33 Chambers Moni Brar 34 What You Want Doesn't Matter Em Fowler 42 Show up Jos' Emilio Pacheco 44 Riverside Drive Translated by Cynthia Steele Tara Borin 55 Father's Day Leah Sandals 56 re:accounting Laura Zacharin 65 The Shloshim T. Dallas Saylor 67 Can't Find It Domenica Martinello 68 Pedestrian E. Kristin Anderson 78 How You Made Me Want Carol Krause 80 losing the world Alice Turski 81 Looking for Jade Rabbit Contributors 90
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.805 | 0.703 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".