Performing Indigenous Well-Being: Historical and Political Geographies of Canada’s Community Well-Being Index
Bibliographic record
Abstract
Set against the view that development indices provide objective assessments of the human condition, in this research, I demonstrate that indices are deeply political and emerge from specific and embodied histories and geographies. This study traces the emergence and subsequent politics of the “Community Well Being Index,” hereafter the CWB, an index designed to measure the conditions of Indigenous communities in Canada that was developed in the early 2000s by researchers at the Department of Indian Affairs and Northern Development in collaboration with social scientists at the University of Western Ontario. Drawing theoretical contributions from performativity scholars, as well as postcolonial, settler colonial and critical development literatures, my research explores how the index, as a historically, socially, technologically contingent tool, actually produces the world it sets out to measure. Through analysis of interviews with designers and users of the index, observation of its presentation, and a review of official documents in which the index is elaborated, I trace the multiple and at times contradictory ways in which the CWB has come to matter in shaping development common- sense, constituting Indigenous subjectivities and allocating responsibility surrounding development interventions. I contend that, notwithstanding its use in advocating for the improvement of Indigenous peoples’ socio-economic conditions, the index is part of a settler policy and bureaucratic performance that predominantly serves to narrow the development pathways available to Indigenous communities.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.024 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".