Bibliographic record
Abstract
This thesis is a regionally rooted, contrapuntal poetry cycle. I intend for it to unite my preoccupations with ecofeminist poetics and the genetic inheritance of fractured, grandmaternal generational lines, reconciling private and public conflicts by examining how political and geographical rupture, war zones, and genocide generate traumatic, ancestral memory. The granddaughter of Holocaust survivors and World War II veterans, my work will ask loud questions about why, for decades, depression has decorated the medical notes of my family, as if the ink stayed wet for a century, rubbing from one manila folder to the next. My project examines where these ancestral memories intersect, and manifest as cyclical bouts of anxiety and depression, physical illness, and disordered eating. By granting these recurring intergenerational cadences value in the present, my poems seek to transform stress, and the legacy of its gifts, into a greater consciousness. I hope my collection will join a canon of texts probing complicated cultural legacy, with an unchartered crispness in Canada.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.046 | 0.016 |
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".