Bibliographic record
Abstract
Tim Bowling was born and raised on the west coast of Canada where he grew up in a salmon fishing family. These early experiences of working in the wild greatly inform much of the writing he has published since 1995. Over the past eighteen years, he has put eleven poetry collections, four novels, and two books of creative non-fiction into the world, and has received numerous accolades: two Governor General's Award nominations, two Writers Trust of Canada nominations, a fellowship from the Guggenheim Foundation, five Alberta Book Awards (ten nominations), two Alberta Readers Choice Awards nominations, and a Canadian Authors Association Award. His work with other writers at various stages of their careers has also been considerable. In addition to teaching at the Banff Centre for the Arts in both poetry and fiction, Tim has served as a writer-in-residence at several institutions and recently completed a term as the online WIR for ARC, Canada's national poetry magazine. Widely respected in both the local and national literary communities (he has lived happily in Edmonton since 1995), Tim continues to work in a variety of writing forms, including fiction, non-fiction, the essay, and poetry.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.015 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".