Self-Employment Trends Among First Nations, Métis, and Inuit (2001–2021)
Bibliographic record
Abstract
This article explores self-employment trends among Indigenous Peoples in Canada between 2001 and 2021, focusing on 2016 onward. Using disaggregated data (i.e., data separated by First Nations, M.tis, and Inuit identity) from Statistics Canada’s Census of Population, it examines changes in both self-employment rates and absolute numbers, revealing distinct patterns across Indigenous groups. The analysis finds that while Metis individuals consistently report the highest self-employment rates, First Nations, despite notable growth, continue to face structural barriers, particularly those imposed by the Indian Act. Inuit remain significantly underrepresented in self-employment. The article also draws attention to the underutilization of external business assistance: in 2017, 88% of self-employed First Nations, 72% of self-employed Inuit, and 91% of self-employed M.tis reported receiving no outside support. These findings underscore the importance of disaggregated data and call for targeted funding models that reflect the diverse conditions shaping Indigenous self-employment in Canada.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".