"Words Hide Truth": National belonging in Marian Engel’s Bear and Tessa McWatt’s Out of My Skin
Bibliographic record
Abstract
The famous problem of Canadian Literature in the contemporary critical landscape is how it, as an institution, denies all but certain kinds of identities. Alexander Beecroft suggests that a national literature, through its attempts to locate and articulate a communal identity and a notion of fellow-feeling, curates characteristics among members of previously numerous groups which can function to denote nationalistic identity. Such a discourse of inclusivity relies on subsuming difference as accidental aspects of a shared identity: that of the national subject. This thesis studies two Canadian novels, Marian Engel’s Bear (1976) and Tessa McWatt’s Out of My Skin (1998), and argues that they employ and subvert specifically Canadian national mythologies and patterns to critique the nature of North American identity-making as constructed for a white, male subject and thus restrictive and often painful for the non-male or racialised subject. Specifically, this study argues that the novels engage with the colonial moment in a critical way, not least through employing and subverting the pioneer-narrative as a manifestation of discursive claim to national belonging. To do this, the discourse theory of Ernesto Laclau and Chantal Mouffe, as well as the theoretical works of Sara Ahmed, are mapped onto the novels protagonists. The central focus of the study is the tension between the protagonists’ bodies and the spaces in which they move, as well as the subjects they encounter. Significant focus is placed on those articulations of or claims to belonging that the protagonists employ, and how they consistently result in failure. The conclusion of the study argues that through such failures of claiming belonging, the novels share an attitude of contingency and materiality towards the concept of national identity which rejects normative attitudes of inclusion and multiculturalism for the sake of a return to moments of identity-making, and the injuries complacent to them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".