Bibliographic record
Abstract
From verses written on shipboard to poetry published by prestigious London presses, from settler tales written to encourage emigration to autobiographical fiction depicting the often daunting realities of colonial life, British women's writing fully engaged with the nineteenth-century empire. In addressing a topic so global in scope, with parameters still very much under construction, our strategy is to provide an outline of genres written by women in the British Empire and then to focus on poetry published by women in Canada, India, Australia, and New Zealand, drawing parallels and outlining divergences among poetic practices in four quite different colonial settings. We focus on gender and colonial poetic practices for three reasons. First, in the literature of empire, poetry remains understudied, though many writers considered it the most prestigious of genres at the time. Writing poetry allowed women to establish local and global relationships of literary sociality through newspaper and subscription publication, even in an environment in which they were patronized as poetesses. Moreover, little comparative work has treated Anglophone poetry in global contexts; our comparative approach suggests further work on colonial poetics as global cultural negotiation. Finally, we argue that formal constraints of writing verse in the nineteenth century created aesthetic pressures that magnified the contradictions and ideological impasses of empire. The poems of Emma Roberts and Mary Leslie in India, of Isabella Valancy Crawford in Canada, and of Eliza Hamilton Dunlop in Australia present cogent examples of this phenomenon. We discuss writings of British women as they traveled or lived abroad and address differences as they emerged in the colonial scene between first- and second-generation writers and between what are commonly distinguished as extraction and settler colonies: that is, colonies the British governed for trade and profit versus colonies British people settled to extend and reproduce their ways of life. We argue that individual cases suggest the limitations of this common antithesis between two kinds of colonial settings. Emigration and settlement, while they appear to result from a straightforward decision, were not always so clearly demarcated from temporary residence or even travel. Many British subjects living in India did not anticipate returning to Britain, a condition common to second-generation residents; conversely, many emigrants to Canada or the antipodes imagined they might one day return “home.” The identity of home itself is vexed by the dislocations attendant on travel, temporary residence, and emigration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".