“Hope, but also Danger”: A Conversation with Larissa Lai on not Going Back and the ‘Re’ of Recuperation
Bibliographic record
Abstract
Larissa Lai is a poet, fiction writer and academic who holds a Canada Research Chair at the University of Calgary, where she directs The Insurgent Architects’ House for Creative Writing. She has authored nine books. Her most recent works are The Tiger Flu, Iron Goddess of Mercy and The Lost Century. She is a recipient of the Jim Duggins Novelist’s Prize, the Lambda Literary Award, and the Otherwise Honor Book. She was recently awarded a Maria Zambrano Fellowship at the University of Huelva in Spain and has been actively engaged in cultural organizing, experimental poetry and speculative fiction communities since the 1980s. Her work often explores themes of identity intertwined with elements of science fiction and the fantastical imagination. This interview took place in Parque García Sanabria on 24th March 2023 during a visit of Larissa Lai to the University of La Laguna. This interview focuses on the convergence of history, myth and affects, providing a reflection on the circularity of time and the promise of happiness.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.051 | 0.025 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.016 |
| 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".