Contemporary evacuation responses in a Northern Saskatchewan Cree community: the residential school analogy
Bibliographic record
Abstract
In this article, we chronicle the experiences of a northern Cree community in Canada which undergoes an emergency evacuation due to threat by wildfire. Forced to leave their community under short notice as the fire encroached, individuals were triaged for “risk” and removed sequentially to different communities and temporary facilities. The process of evacuation prompts comparison with earlier processes of the forced removal of children to residential schools. The analogy is based on two experiential domains. First, families were fractured, with members being separated. Elders were placed in lodging apart from other family members, and in some case family members were sent to different towns. Second, the residents experienced a loss of agency in all aspects of the evacuation, from declaring the emergency to governing themselves in evacuation centers. We argue that disaster response policy as it pertains to Indigenous communities must embrace an acute awareness of the consequences of state oppression and forced assimilation, assumed to be only historical, that shape experiences involving emergency intervention by contemporary state authorities. Rather than replicating these historical processes, evacuations represent opportunities to engage with Indigenous knowledge and experience to ensure local needs are met in ways that are culturally and experientially safe.
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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 | 0.030 | 0.019 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".