(Re)mediating History in Canadian Auto/biographic Long Poems since 1970
Bibliographic record
Abstract
Responding to current topics of national debate around cultural appropriation, authenticity of voice and identity, historical commemoration, and foundational systems of social injustice, this dissertation takes as its launching point the question of how we are implicated in each other's histories. It examines the politics of rewriting history in Canadian auto/biographic long poems from 1970 to the present, reconsidering historiography as it intersects with life writing, gender, race, and the performance of voice. What narratives are reimagined about the lives of Canadian historical figures, how are such stories articulated, and who is permitted to perform the telling? As a whole, the poems I analyze demonstrate skepticism of official national narratives, some working to unsettle and undermine these histories by advancing counterhistories and others functioning as recovery projects to re-present the lives of nearly forgotten or historically marginalized figures. A critical thread that can be traced throughout the chapters is the necessary ethical engagement of both poets and readers: issues this project wrestles with include the role of memory and forgetfulness in the nation's privileging or overlooking of particular stories, the effects of poets commandeering the speaking "I," and the sometimes challenging task of ascertaining the division between appropriation and appropriate representation.\nThe work of remediating the past is a project not only the CanLit community is currently deeply invested in, but also the Canadian public, as demonstrated by ongoing widespread conversations about what histories and systems of belief we honour in our chosen place names and by the difficult yet vital unburying of traumatic Indigenous histories as we confront the devastating evidence and lasting harm of federally endorsed assimilation policies. Ultimately, this dissertation makes the case that Canada is at a critical point in its national narrative when, after striving to define a national identity in the previous century, its citizens are in the process of re-evaluating its historical foundations, its cultural texts, and the identity it projects to the rest of the world. With the nation under an international media spotlight due to the global revelation of its violent colonial history, we need to continue the difficult cultural work of confronting and reassessing our perceptions of Canadian histories, and the kinds of rebellious and recuperative texts featured here are uniquely positioned to aid in this important task. The primary texts analyzed are long poems by Robert Kroetsch, Margaret Atwood, Jan Horner, Syd Zolf, Stephen Scobie, Gwendolyn MacEwen, Joan Crate, Armand Garnet Ruffo, and George Elliott Clarke.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.029 | 0.029 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".