Indigenous Procurement as a Catalyst for Community Building
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
From 2018 to 2021, a series of Indigenous Procurement Engagement sessions (IPE-sessions) took place in-person and virtually in Ottawa and Toronto to explore the modernization of Indigenous procurement in Canada. Stakeholders from regional and national Indigenous organizations, Indigenous and non-Indigenous business leaders in the private sector, as well as federal government officials, participated in the engagement sessions. In total, there were 98 participants (n = 98) for all the engagement sessions (28 in 2018; 49 in 2020; and 21 in 2021). This research re-analyzes data collected from 2018 to 2021 and aims to answer the question—can Indigenous procurement be a catalyst for community building? The research re-analyzes the data through the exploration of 4 main chapters: 1) Building Strong First Nations Economies: Economic Development, Community Building, and Procurement; 2) Social Procurement Policy and the Inclusion of Diverse Supply Chains. Is Indigenous Procurement ‘Social Procurement’? 3) Challenges and Wise Practices for First Nations Procurement in Canada; and 4) Should Indigenous Procurement be Legislated? Federal Indigenous Procurement Policy Versus Article 24 of the Nunavut Agreement. The research findings indicate that procurement is a catalyst for First Nations community building as local procurement contributes to community prosperity through business development and growth, job creation, and community wealth building, as well as other social outcomes, which are defined by First Nations communities, organizations, and businesses.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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