Write from the Heart: An Interview with Brian Wrixon, a Poet from Canada
Bibliographic record
Abstract
Brian Wrixon, a poet, was born in 1946 in Toronto, Canada. He graduated from Laurentian University in Canada with a degree in Classical Studies, and is a former faculty member, online curriculum design consultant and program coordinator at Mohawk College in Hamilton, Ontario. His working career in the financial services business spanned forty years. He has contributed his poems to numerous collections of poetry. Apart from this, as a poet, he has written Poetry in Motion Volumes 1 & 2 (2011), Confessions of a Would-Be Poet (2011), Heartbeats, Footsteps & Musings (2012), Doors (2013), Down to the Sea in Words (2013), The Moving Finger Writes (2013), Sculptured Words (2013), A tisket, a tasket, poems in a Basket (2013), It’s a Sign of the Times (2013), Nightmares & Dreams (with Rollie Mukherjee) (2013),Shoot From the Hip: Memories of a Small Town (2013), A Return Ticket: Memories of Leaving a Small Town (2013), My Passage to India (2014), A Look at Yesterday (with Robert Vincent) (2014), Our Town Revisited (with Robert Vincent) (2014) and Desperate Freedom: a Play in Four Acts (2014). Apart from composing a good number of poems, he has edited many anthologies of poems and operates as a publisher as well. In addition to writing and publishing numerous poetry and prose works of his own, he has been instrumental in assisting hundreds of young and emerging authors from around the world get published, either personally or as contributors to group anthologies.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.080 | 0.023 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.022 |
| Insufficient payload (model declined to judge) | 0.008 | 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".