Okanagan story and Women in the woods: a critical reflection on pioneer women and their legacy in Canadian literature
Bibliographic record
Abstract
AN OKANAGAN STORY: A NOVEL Historian Mike Dunbar is at a crossroads in his career: it’s publish or perish. He chooses publish, his subject: Scottish Settlers in the Okanagan, British Columbia, a fertile valley in the shadows of the Cascades, known for the lake, bountiful orchards, trendy vineyards, and pioneers, specifically, JD Ballantyne. JD is either an enterprising settler or criminal arsonist; nobody seems to know which anymore. But then Mike gets an email from Haley Gibson, JD’s great-great-great-granddaughter. She’s just lost her mother, her connection to the past. Soon, the two find they have more in common than JD. As Haley gets stuck unravelling her complicated family history, and Mike gets closer to solving the mystery of JD, will the answers be the ones they’re looking for? And can their connection survive a breakup, family expectations, major life decisions, and the truth about JD Ballantyne’s life and misdeeds? An Okanagan Story is a novel about Canadian family folklore, dealing with grief, and the realities of just getting by in a sometimes hostile world. WOMEN IN THE WOODS: A CRITICAL REFLECTION ON PIONEER WOMEN AND THEIR LEGACY IN CANADIAN LITERATURE This project examines how the pioneering experiences recounted in Susanna Moodie’s Roughing It in the Bush and Susan Allison’s ‘Recollections of a Pioneer Woman’ contribute to the creation of the pioneer woman character, traditional stories about ‘Canadianness,’ and tropes that form a large part of ‘CanLit.’ The essay explores the ways both authors use the form of memoir, contemplating Sidonie Smith and Maggie Pickering’s writing on how memoir allows women to write about their experiences in male-dominated spaces and overcome barriers that restricted women in the 19th century. The essay also examines how Moodie and Allison become ‘literary foremothers’ to Canadian authors by examining Margaret Atwood’s The Journals of Susanna Moodie, a narrative poem sequence which reframes Moodie’s experience of pioneer life from Atwood’s 20th century urban Canadian perspective. Finally, the essay asks why the story of the pioneer woman continues to appear in ‘CanLit’ despite the loss of the rural backwoods, utilising Helen Thompson’s idea of a ‘shifting frontier.’
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.113 | 0.053 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.007 | 0.011 |
| 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".