Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A dynamic dialogue of poetry and art that reimagines the ancient, biblical concept of sacrifice. Winner of the 2022 Gerald Lampert Memorial Award presented by the League of Canadian Poets A collaboration between poet Alisha Kaplan and artist Tobi Aaron Kahn, Qorbanot -the Hebrew word for "sacrificial offerings"-explores the concept of sacrifice, offering a new vision of an ancient practice. A dynamic dialogue of text and image, the book is a poetic and visual exegesis on Leviticus, a visceral and psychological exploration of ritual offerings, and a conversation about how notions of sacrifice continue to resonate in the twenty-first century. Both from Holocaust survivor families, Kaplan and Kahn deal extensively with the Holocaust in their work. Here, the modes of poetry and art express the complexity of belief, the reverberations of trauma, and the significance of ritual. In the poems, the speaker, offspring of burnt offerings, searches for meaning in her grandparents' experiences and in the long tradition of Orthodox Judaism in which she was raised. Kahn's paintings on handmade paper, drawn from decades of his career as an artist, have not previously been exhibited or published. They reflect his quest to distill a legacy of trauma and loss into enduring memory. With a foreword by James E. Young and essays by Ezra Cappell, Lori Hope Lefkovitz, and Sasha Pimentel, the book presents new directions for thinking about what sacrifice means in religious, social, and personal contexts, and harkens back to foundational traditions, challenging them in reimagined and artistic ways.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it