Race, gender, and the exotic in Ann-Marie MacDonald’s <i>Fall on Your Knees</i>
Bibliographic record
Abstract
Focusing on Canadian author Ann-Marie MacDonald’s critically acclaimed Fall on Your Knees (1996), this essay argues that the figure of the Arab in the novel represents an ethnic otherness whose strategic exoticization exposes a highly racialized and gendered early twentieth-century North American culture, one that has historically been informed by a latent, economically motivated exoticism. It is in fact this underlying exoticism that has persistently structured the experiences of several generations of racial and sexual minorities in North America and relegated those minorities to the margins of social life. MacDonald’s novel thus deserves renewed attention precisely because it traces critically the historical continuum along which exoticist constructions of race and gender have shaped the experiences of many immigrants in North America. Only by attending to the cultural politics of the exotic, I want to suggest, can we open up discourses of race and gender to productive and transformative cultural critique.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.030 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| 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".