Myth, memory, and narrative : (re)inventing the self in Canadian fiction
Bibliographic record
Abstract
In this dissertation, I examine how the themes of memory, storytelling, and the construction of narrative identity develop in the works of Canadian authors Alistair MacLeod, Michael Ondaatje, and Jane Urquhart. As a means of delving more deeply into these themes, I focus on the specific narrative strategies that all three writers employ in the expression of the relationship between the individual and his/her community, as well as between physical and psychological realities. For the narrative voices in these authors’ works—given the different ways they envision and encode communal identity as constitutive of subjectivity—the past is inextricably embedded in the present. As they construct and record unfolding experience, a wider cultural history is written over with personal connections and significance. In the works of each of these authors, the act of telling stories (re)shapes people and events for the audience: speakers reform and reconstitute their experiences, allowing them both to rewrite the past and be haunted by it. Storytelling becomes an existential act in which personal landscapes are invested with structures of feeling that transcend local significance yet are manifested in everyday connections between ordinary people, and in daily (often unrecognized) struggles and acts of heroism. This includes a study of the means through which psychological evolution and trauma can be depicted. I also discuss how stylistic techniques such as fragmentation, repetition, self-reflexivity, and literary allusion function within these narratives. This aspect of my investigation provides the opportunity to engage more fully with the body of literary research that has already been produced on these authors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.029 | 0.033 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".