Bibliographic record
Abstract
"Noble's work has always engaged, in its own way, with the Western Canadian tradition of poetry as intellectual experiment grounded on local experience.… Death Drive marks a counter-turn in the work of one of Southern Alberta's most distinctive writers." - Chris Jennings, Department of English, University of Ottawa In this collection of poetry, Charles Noble further reins in an already tight form - haiku - only to let loose a "logopoeic" poetry. He presents poems of extraordinary rigour and riddles of wit that are solved by "lifetime" insights - a dialectical poetry that still observes a phenomenological toehold but transcends the limits of locality in recognizing the curled-up-but-everywhere world of media and markets - à la Fredric Jameson. And yet, these "haikus" go straight - to "the shock of the naïve." They turn to a middle ground, in Aristotle's sense of difficult target. They point to human acts, human reactions, and enact, themselves, a meta-linguistic wrestling, at one with the quarreling couple in the bar hanging on each other's words and insistent with "what do you mean by [a simple word]?" But they are also implicated in what he calls the death drive (not death wish), which arcs freely over a human life span - think architecture - and which, more radically, in the "pleated/ crossword," "make[s]/ good// a/ bit/ of/ bad/ infinity," no expenses, save for that toehold, earth, as he would have it.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.929 | 0.922 |
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".