Building Better Together: Exploring Indigenous Economic Development in New Brunswick Report
Bibliographic record
Abstract
This project, titled "Building Better Together: Exploring Indigenous Economic Development in New Brunswick", sought to ask: What does Indigenous economic development mean to Indigenous Peoples living in New Brunswick? In doing so, it attempts to identify obstacles, opportunities, and priorities to achieve these development goals. With support from an Indigenous Research Capacity and Reconciliation Connection Grant from the Social Sciences and Humanities Research Council (SSHRC), this project brought together 130 frontline representatives from Indigenous communities, organizations, and businesses with those from academia and relevant provincial and federal departments for a Mawi'omi (meaning 'gathering' in Mi'kmaq) in May 2019 to explore these questions. In large part, this initiative validates previous research on Indigenous economic development specifically, and Indigenous development more broadly. A majority of the participants identified that self-sufficiency and self-sustainability for Indigenous communities were the most important factors for successful community development, with long-term stability the second most important factor. Three factors were tied for third: revitalizing language and culture, providing employment and training opportunities to members, and improving community wellness and cohesion. Key priorities for economic development were the creation of employment opportunities and the development of workforce skills, as well as the development of lands and infrastructure for economic development, while key opportunities were the cannabis, tourism, natural resources, and renewable resource sector. And finally, key challenges to the pursuit of Indigenous economic development were financing, human resources, and social issues. Throughout the event, participants also emphasized the need for more meaningful and respectful relations with government and the private sector. Resulting from this research, several recommendations were identified that support the findings above. These recommendations target three main groups: to SSHRC, continue to offer annual grants specifically for Indigenous communities and organizations, to support the creation of diverse research products relating to Indigenous economic development, and to create or support a platform to share information and resources relating to Indigenous economic development; to the federal government, increase funding for economic development for First Nation communities and Indigenous organizations; to the provincial government, create a task force to increase the inclusion of First Nation communities and Indigenous Peoples in the tourism, cannabis, natural resource, and renewable energy sectors; and to First Nation Communities in New Brunswick: develop strategies to support self-determination, self-sufficiency, and economic development.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".