Displacement of Indigenous People in Canada under the Indian Act: Participatory Video with Lake St. Martin and Little Saskatchewan First Nations on Flood Impacts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Four participatory video research projects were undertaken over eight years with two Indigenous communities displaced by a flood. The films focus on how floodwaters were diverted away from non-Indigenous regions to Indigenous communities at Lake St. Martin by Canada’s colonial government. This displacement repeats the colonial pattern of forcibly relocating Indigenous people away from their land, resources, and good life. This participatory video research of flood stories underwent a content, process, and outcome analysis. The environmental, social, cultural, health and economic impacts are documented in the films, including poverty, environmental injustice, gang predation, separation of families, food insecurity, illness, culture loss, addictions, and racism. The films captured the lived experience of Elders, youth and, families during their eight years of displacement to temporary, unsuitable accommodations and upon relocation. In terms of process, community members engaged in filming, scriptwriting, and narrating to tell their stories. The process was transformative, decolonizing, and built community research capacity. The participatory video research was helpful for lawyers advocating for compensation. The popularity of the videos online exceeded that of academic papers and helped fuel a movement to wake people to the ongoing colonial injustices faced by Indigenous people across Canada. This paper not only analyzes the films but traces the roots of Indigenous displacement by man-made flooding to the Indian Act and colonization, calling for abolishing the Indian Act and decolonization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.004 | 0.000 |
| 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 it