Black Women's (Im)Mobilities: Memory, History and Diasporic Entanglements
Bibliographic record
Abstract
In June 2023, Prof. Andrea A. Davis (York University) was invited to hold the sixth Vienna Lecture in Canadian Studies at the University of Vienna. In her lecture, Andrea A. Davis returns to the trope of the sea, pivotal to the thinking in her book Horizon, Sea, Sound: Caribbean & African Women's Cultural Critiques of Nation (2022), to trace the contours of Caribbean women's crossings from West Africa to the Caribbean, Canada and Europe through the archive of the ships that connected enslaved Africans and indentured Indians with the Indigenous peoples of the Americas. Turning to the work of Camille Turner, M. NourbeSe Philip, and Ramabai Espinet—Caribbean artists writing from Canada—Davis re-narrates the white settler state as a Black diasporic space, linking Canada not only to the Caribbean but also to West Africa. She considers how these artists cross physical, imaginative and spiritual borders to articulate the terms of their being in place. Davis theorizes this raced and gendered understanding of Caribbean women's diasporic journeys in four movements through a series of overlapping journeys that extend from Newfoundland, Canada to Gorée Island in Senegal; Gold Coast in present day Ghana to Black River, Jamaica; St. Helena off the coast of southwestern Africa to Trinidad and Tobago; and Guyana back to Canada. These multiple and sometimes unexpected movements help to illustrate the deep imbrications of Black people's interconnected journeys.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.021 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".