Collaborative Aboriginal Economic Development: The Unama’ki Economic Development Model
Bibliographic record
Abstract
The environmental impact of this industry included "more than a million tonnes of contaminated soil and sediment" deposited in four areas in the vicinity of the former steel mill: "North and South Tar Ponds; Former Coke Ovens property; An old dump uphill from the Coke Ovens; [and] A stream that carried contaminants from the Coke Ovens to the Tar Ponds" (Sydney Tar Ponds Agency "Project"). The UEBO has grown to include seven full-time staff members, including an executive director, a director, a training coordinator, two training support/job coaches, a finance officer, and an administrative assistant (Unama'ki "Contact"). Since the UEBO responds to the needs of the communities and other stakeholders, staff positions are added or removed as necessary. A Priorities and Planning Committee representing the Sydney Tar Ponds Agency and the local First Nation communities is comprised of the president of the Sydney Tar Ponds Agency, a senior federal representative of Public Works and Government Services Canada (PWGSC), a senior provincial representative of Transportation and Infrastructure Renewal, and the executive body (co-chairs of the steering committee and executive director and director of the UEBO). The ASEP board consists of the five Unama'ki chiefs; representatives of Public Works and Government Services Canada, the provincial Department of Labour, the Sydney Tar Ponds Agency, Ulnooweg Development, and Mi'kmaq Employment Training Secretariat (METS); senior industry representatives; the executive body (with executive director and director of the UEBO ex officio); and a representative of Human Resources and Skills Development Canada (ex officio).
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".