Successful Development in Aboriginal Communities : Does it Depend upon a Particular Process?
Bibliographic record
Abstract
This article brings needed attention to the process of structural change in Aboriginal communities, which has been largely neglected in current policy and practice on economic development and good governance. New research strongly suggests that generalized trust (social capital), and a capacity to discuss rather than suppress conflict (social cohesion), are crucial to long-term success in economic development and self-government. Likewise, trust and effective conflict resolution are built or undermined by the process by which structural changes (e.g., economic, governmental) are made and implemented. Processes most likely to support long term success of structural changes in Aboriginal communities: (1) are grounded in a commitment to mutually acceptable cultural values, (2) develop working relationships across subgroups before making substantive decisions, and 3) actively include the participation and concerns of interest groups across the community. Success in partnering with Aboriginal communities for economic and political development is most likely when a balance of attention is paid to the process as well as the structure of change, and to the identity needs, as well as the practical needs, of the community.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.028 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".