Socioeconomic framework and indicators for assessing cumulative effects of resource development on indigenous nations
Bibliographic record
Abstract
• The development of natural resources, particularly mining and associated infrastructure, has profound impacts on ecosystems and people, particularly on host communities, with Indigenous Nations often bearing disproportionate burdens. • Cumulative effects are inherently politically wicked problems that require careful management of power imbalances, but at the same time need to be guided by the best available knowledge and science from both Indigenous and non-Indigenous people. • Mainstream impact assessments continue to be disproportionately directed towards evaluating only the biophysical impacts, usually neglecting the critical aspects of Indigenous worldviews and ways of knowing and being. • We propose five domains and associated indicators for assessing the cumulative impacts of mining on Indigenous Nations and local communities, including social/community wellbeing, economic impact, human health, cultural wellbeing, and governance. • Our approach aligns with the emerging recognition that practical assessments of long-term environmental changes require the integration of diverse knowledge systems. The development of natural resources, particularly mining and associated infrastructure, has profound impacts on ecosystems and people, particularly on host communities, with Indigenous people often bearing unequal burdens. Mainstream impact assessments continue to be disproportionately directed towards evaluating mostly biophysical impacts, usually neglecting the critical issues of cultural, social, health and economic aspects that impact Indigenous ways of knowing and being. In this paper, we provide a conceptual contribution to the search for a holistic socio-economic assessment of the cumulative impacts of resource development on Indigenous people. Drawing upon existing research and direct engagement with Indigenous people, we propose a holistic framework for regional cumulative socio-economic effect assessments of resource development. We anchored our framework in the concepts of environment, place, and space linked to the Indigenous concept of wellbeing. To operationalize the framework at the regional level, we recommend building Indigenous representation and capacity by adopting Indigenous governance systems, legal principles and values based on the concepts such as the mino pimatisiwin . Our approach provides a holistic, relational, interrelated, and interdependent view that is culturally sensitive, responsible, and reciprocal and provides a relevant foundation for selecting appropriate socio-economic indicators to assess regional cumulative effects of mining on Indigenous people.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".