THE PLACE OF FIRST NATIONS GENDER IN DISASTER EVACUATION POLICY IN SASKATCHEWAN AND CANADA
Bibliographic record
Abstract
Globally, Indigenous communities have a history of disproportionate risks of exposure to disasters and emergency evacuation, rooted in historical marginalization and enduring colonial legacies. In Canada, the word Indigenous includes three groups of people: the Inuit, Métis and First Nations people. Although Indigenous communities as a whole experience the disproportionate disaster impacts, Indigenous women, including First Nations women and girls, face an additional burden due to socially constructed gender and caregiving roles during emergency evacuation. This research examines federal and Saskatchewan provincial emergency management (EM) policies through a critical discourse analysis (CDA) and manifest content analysis (MCA) framework to assess the extent to which these policies recognize First Nations women and girls as well as the discourse practices within policies and the disparity between federal and provincial policies. By analyzing federal and Saskatchewan emergency policies, this study highlights the absence of policy recognition of First Nations women and girls. The findings indicate that both federal and Saskatchewan provincial EM policies recognize Indigenous communities broadly but do not address the risks faced by First Nations women and girls. Saskatchewan's policies offer minimal and indirect recognition, lacking gender-sensitive approaches and largely excluding Indigenous governance from decision-making. While acknowledging Indigenous engagement, federal policies frame their role as advisory rather than leadership, reinforcing a top-down governance structure. Both policy levels prioritize infrastructure resilience and regulatory compliance over culturally responsive and gender-inclusive EM. Further, the language used in these policies perpetuates a dependency narrative, positioning Indigenous communities as recipients of emergency assistance rather than self-governance in disaster response. In addition, it demonstrates that systemic inconsistencies exist between federal and provincial policies, undermining effective EM, as both levels do not operationalize their rhetorical commitments to Indigenous engagement, especially First Nations women and girls living on reserve in Saskatchewan. This research recommends that a shift toward Indigenous-led, gender-sensitive, and culturally responsive emergency frameworks incorporating gender-based analysis, Indigenous self-governance, and culturally appropriate policy language is essential to enhancing the inclusivity, effectiveness, and resilience of EM policies for First Nation women and girls in Saskatchewan, Canada.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| 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".