Bibliographic record
Abstract
A visceral new collection from esteemed poet Stephan Torre, grappling with the strength and complexities of life in the northwest wild lands. Drawing from a life lived well, amidst hard work and time for reflection in the northwest wild lands of the Canadian and American Wests, Stephan Torre returns to the literary world with his usual descriptive and lyric intensity. Comprised of new and selected poems, Red Obsidian explores the necessary tensions that arise between genders and the pain and grief of environmental loss. Inspired and influenced by a diverse array of literary influences—Indigenous oral poets and English pastoral poets, T’ang Dynasty Chinese poets and Latin American poets, American Imagists and poets Theodore Roethke, James Wright, and W.S. Merwin—Torre’s book is a poetic journal of a man passionately engaged at once with the marvel of wilderness and the rural labours of family homesteading, construction, and the logging of that wilderness. “When there’s more joy or grief or hunger for knowing than I could express or explore elsewhere, I’m afflicted with the need to squeeze language from my fists. One can only hold so much inside,” admits Torre. Readers will feel the torque, squeeze, and pull in these poems.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.360 | 0.169 |
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".