Bibliographic record
Abstract
When poet and broadcaster Mona Gould died in 1999, she left behind thirty-eight boxes of papers. Her war poem, "This Was My Brother," was still a staple of textbooks and anthologies, yet Mona - well known in her youth - had fallen into obscurity in the 1960s. Born at the very time Mona's career was faltering, Maria Meindl became a captive audience for her grandmother's extravagant stories of the past. Years later, Maria took on the daunting task of sorting through Mona's mountain of papers to create an archive for the University of Toronto's Fisher Rare Book Library. The chaotic state of the boxes reflected Mona's flamboyant and demanding personality, yet they also drew an important picture of the life of a Canadian freelancer in the twentieth century. Mona had begun publishing poetry and features in newspapers in the 1920s and published three books of poetry in the 1940s. In the 1950s, at a time when many women were retreating from the public sphere, she had a successful radio career. Her later journals and letters recount, in agonizing detail, a downward spiral into self-doubt, poverty, and addiction. Maria soon discovered that the truth of Mona's life was even more fascinating than her stories. Outside the Box brings to life a thinly documented era in Canadian letters through the story of one passionate and conflicted woman. It also charts the journey of an unwilling archivist, coming to terms with family secrets, forgotten history, and the stories that are never told.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.734 | 0.625 |
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".