Dwelling in the Human/Posthuman Entanglement of Poetic Inquiry: Poetic Missives to and from Carl Leggo
Bibliographic record
Abstract
This inaugural Dr. Carl Leggo Memorial Lecture on Poetic Inquiry was delivered at the 7th International Symposium on Poetic Inquiry on October 3rd, 2019. I share a poetic conversation I have crafted out of Carl’s work that allows me, and all of us, to enter into a continuing dialogue with Carl’s words, which survive and will live on without his earthly presence. I discuss the process I undertook to create these poetic missives, in my voice and Carl’s, following the dialogue. All of the work beginning with “Dear Monica” are found poems created from Carl’s writing—his prose, not his poetry. My own poetic messages to Carl are mostly original, although they include a bit of found poetry from the literature on posthumanism. And the abecedarian poem is definitely inspired by Carl’s love of this type of poem, and his playful joy, always, in exploring the possibilities of language and poetry.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.027 | 0.041 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.005 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 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".