'Thinking Themselves Halved when they are Atomized': Identity Contradictions in Marian Engel's <i>No Clouds of Glory</i> and <i>The Honeyman Festival</i>
Bibliographic record
Abstract
This article focuses on Marian Engel's first two novels to explore why critics were so often disappointed in her work. Engel's focus on individual female and national consciousness within social and historical circumstances was generally considered a good start, but she apparently took a wrong turn when she did not discover workable identities in an era of dominant Canadian nationalist and second-wave feminist identity movements. Engel resisted the idea of discoverable identity, and the reception of her work suffered. Her less optimistic treatment of identity stands up better today, when we are less sure about the existence of resolvable identities at all. Re-reading these two novels as explorations of obstacles that interfere with identity reveals a compelling pattern: characters are confronted with what troubles their understandings of themselves as women and Canadians.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.052 | 0.071 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.009 |
| 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".