Charmaine Nelson, Slavery, Geography and Empire in Nineteenth-Century Marine Landscapes of Montreal and Jamaica, London, 2016
Bibliographic record
Abstract
Caribbean plantation landscapes have primarily been staged in art historical studies as ‘unique’ sites of troubled artistic negotiations between European notions of the picturesque, and slippages of the reality of enslaved labour and creole culture. Charmaine Nelson reframes these landscapes, by reading together two geographically remote locations, Montreal and Jamaica, as intertwined through colonial authority, trade and the movement of people. She argues that the ideological and visual processes of ‘landscaping’ these localities operated under the same strategies of ‘whiteness,’ nonetheless with different interested outcomes, made legible in various media such as paintings, aquatints and drawings. The urgency she places on this material is clear, as she asks: ‘how do landscape representations produce ways of knowing that are dangerous for how they have naturalized Western understandings of land as universal?’ Her inclusion of Northern locations to the colonial and slave holding imaginary is significant, and arguably opens the field to cross-comparisons also between Europe and the Caribbean. This review asks whether Nelson’s book overstates the ideological homogeneity and coherence of these visual practices and suggests that a closer attention to cartography would make explicit her invocation of geography.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".