The Remainder: Social Collage and the Four Discourses in (some of) the Kootenay School of Writing: Part II
Bibliographic record
Abstract
Note: This essay is from a larger work on the poetics and poetry of the Kootenay School of Writing, the body of work primarily being that published in the 1980s, the approach being a Lacanian one. I divide the poetry into three camps or tendencies: the Red Tory neopastoralism of Lisa Robertson, Christine Stewart, Peter Culley, and Catriona Strang, the concerns of procedural constraints and Blanchotesque absence in Susan Clark, Kathryn MacLeod, Dan Farrell, and Melissa Wolsak, and, here, the social collage/disjunctive form to be found in the work of Colin Smith/Dorothy Lusk (discussed in the first half of this essay) and Deanna Ferguson/Jeff Derksen/Gerald Creede (discussed in this, the second half). Thanks to Donato Mancini, whose research in 2008 greatly helped to kick-start this writing.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.041 | 0.076 |
| Scholarly communication | 0.023 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".