Informing Canadian Innovation Policy Through a Decolonizing Lens on Indigenous Entrepreneurship and Innovation
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
While Indigenous entrepreneurship is associated with significant economic promise, Indigenous innovation continues to be invisible in Canadian policy contexts. This article examines how Indigenous entrepreneurial activities are framed in government policy, potentially leading to another wave of active exploitation of Indigenous lands, peoples, and knowledges. The article first discusses the concepts of Indigenous entrepreneurship and innovation through a decolonizing lens, drawing links to education. Then, it provides a set of rationales for why governments need to re-think and prioritize Indigenous entrepreneurship. Next, it maps the current federal government initiatives in this policy sector. Drawing from the Indigenous entrepreneurship ecosystem approach (Dell & Houkamau, 2016; Dell et al., 2017), the article argues that a more comprehensive policy perspective guiding Indigenous entrepreneurship programs should inform Canadian innovation policy. Individual voices from 13 Indigenous entrepreneurs in Manitoba point to three core issues: (a) relationships with the land and the community; (b) the relevance of (higher) education and training; and (c) the importance of cultural survival and self-determination. The article makes an argument for a systemic decolonizing change in how Indigenous innovation is approached in government policyand programs, supported by the work of higher education institutions.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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