Vulnerability Across Borders: <i>Au Nord d’Albany</i> and <i>Absence of Wings</i>
Bibliographic record
Abstract
This article addresses vulnerability in the Americas via a comparison of a Québécois film, Au nord d’Albany (North of Albany; dir. Farley 2022) and an Anglo-Canadian collection of poetry, Arleen Paré’s Absence of Wings (2023). The constituent nation-states represented in these texts have specific relationships to each other and to continental assertions of power; moreover, power and vulnerability within these nation-states—not simply across them—vary significantly. Both the film and the collection revolve around the figure of a Black daughter to a single, white mother who attempts to mitigate elements of vulnerability for their daughter’s sake. Whereas Au nord d’Albany’s contrast between Canada and the United States both reinforces and troubles stereotypical distinctions between these nation-states, Absence of Wings focuses primarily on the racist failings of the Canadian state, while also invoking the United States and Brazil. Borders constitute obvious sites of adjacency, but the nature of this “up againstness” is not the same at every border, or for every border crosser, as uneven relations of hospitality and hostility attest. To different degrees, Au nord d’Albany and Absence of Wings demonstrate that the Canadian nation-state, despite its long-established rhetoric and policies of multiculturalism, presents little difference from other countries of the Americas in the precarity that structures life unevenly. .
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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 | 0.024 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".