A colloquium with Darko Suvin: questions by Russell Blackford, Sylvia Kelso and Van Ikin
Bibliographic record
Abstract
[Extract] Dr. Darko Suvin F.R.S.C. was a full Professor of English at McGill University, Montreal until his retirement in 1999. His distinguished career - as academic, sf critic, writer, and poet - includes co-editing the journal Science-Fiction Studies from its inception until 1980 (after which time he was a contributing editor) and producing three books which the Clute/Nicholls Encyclopedia of Science Fiction describes as "one of the most formidable and sustained theoretical attempts to define sf as a genre": Metamorphoses of Science Fiction: On the Poetics and History of a Literary Genre (1979), Victorian Science Fiction in the UK: The Discourses of Knowledge and of Power (1983), Positions and Presuppositions in Science Fiction (1988). Suvin played a major role in fostering academic interest in science fiction in the USA, and is credited with introducing the concept of "cognition" to modern sf criticism. He was awarded the coveted Pilgrim Award (for services to sf scholarship) in 1979. The following "colloquium" arose when Darko Suvin kindly agreed to be interviewed for Science Fiction. Russell Blackford and Sylvia Kelso joined the editor in submitting a series of questions by email, and Professor Suvin responded as set out below, sometimes answering related questions together.
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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 | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.009 | 0.018 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.014 | 0.025 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".