Jean Lagassé, Community Development, and the “Indian and Métis Problem” in Manitoba in the 1950s–60s
Bibliographic record
Abstract
In the late 1950s, social worker Jean Lagassé oversaw a major survey of Indigenous peoples in Manitoba. His final report adapted the concept of “culture” to the “Indian and Métis problem” and proposed a program of community development to promote integration through acculturation. In doing so, he advocated an integrationist conception of citizenship that emerged as the dominant liberal paradigm for thinking about Canada. Community development was an idea adapted from the Third World. It held that people could be helped to solve their own problems through organization, democratic decision making, and cooperative action. Put into practice by Lagassé in the early 1960s, the technique was largely used in Indigenous communities in northern Manitoba, a region where government and capital also pursued hydroelectric dam construction and industrialized resource extraction. Lagassé intended for community development to catalyze the integration of First Peoples and Métis into liberal democracy and the capitalist economy. However, as events in Cedar Lake/Easterville and Thompson/Nelson House demonstrated, the practice worked instead to redirect political dissent and encourage local remedial social and economic action in the face of colonial dispossession, racism, capitalist social relations, and the unintended result of state-promoted high modernist development in northern Manitoba.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.017 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".