Bibliographic record
Abstract
Glen Lowry, in his paper "The Representation of 'Race' in Ondaatje's In the Skin of a Lion" bases his discussion on the observation that critics tend to view Ondaatje's writing in terms of a progression towards complex issues of "race" and post-coloniality. In contrast, Lowry argues that the matter of "race" forms an integral aspect of Ondaatje's oeuvre and Lowry proposes that In the Skin of a Lion is a key site in the development of Ondaatje's engagement with issues of "race" and the cultural politics of post-coloniality. Focusing on Ondaatje's depiction of Toronto in terms of its complex history of shifting social spaces and his representation of Patrick and Caravaggio as "racialized" figures, Lowry discusses Ondaatje's engagement with whiteness as a social construct. Rather than critiquing Ondaatje's novel for an apparent absence of race-writing, i.e., writing about so-called "visible minorities," Lowry suggests that Ondaatje in fact "reverses the gaze" and throws the question of "race" back on the readers. Adding the figures of Patrick and Caravaggio to the writing of the city, In the Skin of a Lion undermines presumptions about the racial stability and hegemonic power of Toronto 's and ethnic communities. Last, Lowry argues for a more thorough discussion of Ondaatje's critique of nationalism and multiculturalism vis-à-vis the cultural politics of reading and the construction of "whiteness."
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.015 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".