Contagious Im/Possibilities: Infectious Encounters in Austin Clarke’s The Meeting Point
Bibliographic record
Abstract
Set in Toronto, during an era of changing immigration policies under the 1955 West Indian Domestic Scheme and ongoing revisions to the 1952 Immigration Act, Austin Clarke’s novel The Meeting Point (1967) provides an insightful entry point for the exploration of the intersections of race, disease, (post)colonialism, and citizenship. The meeting points in the text call for a critical analysis of the embodied exposures — the instances of bodies' reciprocal infection, inoculation, and staining — described in this story of West Indian domestics working for Jewish families in the 1960s. The cross-racial encounters portrayed in The Meeting Point are transmissions of contagion, in which the virus of colonial and imperial residue — the living histories and effects of violence and oppression — exposes the impossibility of static ethnic identities and the unstable interconnectedness of marginalities transmitted between displaced subjects. The novel's complex treatment of domestic-employer relationships simultaneously echoes and challenges the imperial discourses of public health in order to unveil past and present realities that trouble narratives of national progress. This article examines the metaphor of contagion in The Meeting Point by discussing miscegenation as a form of racial vaccination and the (non)reproductive body of the Other as a subversive contamination of the modern nation.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.058 | 0.055 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".