PLACE AND IDENTITY: Reading From God’s Spider at the Federation Of Humanities And Social Sciences Congress
Bibliographic record
Abstract
Being a guest-writer at the Federation of Humanities and Social Sciences Congress was an honour. I thank the Canadian Association of Commonwealth Language and Literature Studies (CACLALS) and the Association for Canadian and Quebec Literatures (ACQL) for hosting me to read from my new volume, God’s Spider (Peepal Tree Press, UK)–a shortlisted finalist for the Guyana Prize for Literature (Best Poetry Book category). Indeed, a reading is always a special occasion for me; it’s also a time of liminality–in-betweenness, if you will-- placelessness, a void, quest, looking or yearning for an identity; and being nowhere, but searching. Wanting. As a preamble to my reading, I touched on W.H. Auden’s view that a poet should “mythologize the ground on which he walks.” Having now lived for over four decades in Canada, I am well equipped to do this: mythologizing Canada, sometimes with post-colonial verve and style, or angst. Post-colonial, presumably because all art is political (see Salman Rushdie’s essays in his Outside the Whale).
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".