Postmodernism's defeat beautiful losers and prochain épisode as postcolonial works
Bibliographic record
Abstract
This thesis investigates Leonard Cohen's Beautiful Losers and Hubert Aquin's Prochain épisode in terms, of postcolonial and postmodern theory. These novels are often interpreted as being either one or the other. Critics rarely take into consideration that both of these works have features which can be seen to fit both theories. Both of these authors are valued as some of the more difficult novels to comprehend in terms of Canadian novels making this thesis even more complex and a challenge to write. It made sense to choose to investigate these two works side by side because they have a lot of similarities. Some of these resemblances range from aspects as basic as the time period when the novels were written to the author's methods of using history to make social commentary. It was also important to use two writers from Montreal, each from one of the two solitudes, in order to explore how their novels fit postmodern and postcolonial theories. This theoretical thesis attempts to show how both Leonard Cohen and Hubert Aquin do not use their writing for a nihilistic purpose. Each author uses historical situations to display a hope for new beginnings in the future. Despite all of the literature that exists on both Leonard Cohen and Hubert Aquin, this study tries to show a different interpretation then what has already been done.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.035 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".