From Lady Jane Franklin to #TradWife: gender, race, and class in colonial complicity in the North American High North
Bibliographic record
Abstract
White supremacy's entanglement with gender and class in North America shaped legacies of policies and dynamics toward ordering individuals in hierarchies of desirability. In so-called Canada and the USA, colonial complicity by white women reflects ideals of womanhood intertwined with whiteness and expected roles within the workforce and bourgeoisie. Justifications of settlement and eradication of Indigenous peoples relied on racial superiority using white femininity as a symbol of a Manifest Destiny. The article argues that Lady Jane Franklin's, Louise Arner Boyd's, and Sarah Palin's instrumentalization of their societal positions show the evolution of how race, class, and gender are articulated within the racial-patriarchal-colonial myth-making of the Arctic : from an Angel in the House serving the memory of a British Navy officer ; to an Arctic Diana self-funding her scientific expeditions and collaborating with the government during war; to normalization by claiming nativeness to the land. Palin, Franklin, and Boyd are elite white women who served the crafting of the Arctic within this imperial colonial realm. They operated a carefully well-thought-out strategy balancing the reality of the societal structure in which they lived and live in with their interests and ambitions - embodying the site of contestation between agency and structure.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.043 | 0.022 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".