Constructions of home: the city as a site of spatial history and post-settler identity in four Commonwealth novels
Bibliographic record
Abstract
As a high place of history, culture, and memory, the city bears witness to its past and serves as a record, artefact, and memorial par excellence. Within twentieth-century literary fiction, the spatio-temporal network of the city provides a model for the relativistic nature of identity and historical knowledge. With reference to four postcolonial Commonwealth novels---David Malouf's Johnno (1975), Ian Wedde's Symmes Hole (1986), Michael Ondaatje's In the Skin of a Lion (1987), and Anne Michaels's Fugitive Pieces (1996)---this study focuses on the "chronotopic" image of the city in relation to post-settler and immigrant constructions of "home" in Australia, New Zealand, and Canada. Two distinct attitudes toward urban culture, revealing different models of nationhood and identity, emerge in these works. In the context of multiculturalism, the cosmopolitan city is predominantly treated as a space of tolerance and belonging. Ondaatje and Michaels figure immigrant Toronto as a site of self-discovery in which the bounds and bonds of community are constantly subject to renegotiation. In contrast, disaffection for the modern metropolis is expressed in Symmes Hole and Johnno. This distinction can be framed in terms of a modernist resistance to---as opposed to a postmodernist celebration of---fragmentation, indeterminacy, and heterogeneity. From this perspective, postindustrial urban culture signals the loss of an "original," "authentic" connection to place and hence a severing of the roots of identity. For Wedde, the dystopia of the simulacrum city is a consequence of capitalist imperialism. Malouf likewise laments the superficiality and uniformity of the contemporary urban landscape, however his nostalgia for the unique city of his childhood is arguably founded less in a critique of neocolonialism than in a psychic longing for plenitude and unity. While these urban portraits foreground a number of marginalized voices, there are two main problematic areas of representation. Indigenous spatial history tends to be either excluded or appropriated due to the focus on the "newcomer's" homecoming. Furthermore, space is frequently gendered---such that the female body is made to bear the weight of representing domestic and intimate zones---reflecting the conflation of "home" and the "maternal" in these masculinist quest narratives.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.025 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".