Essential components and pathways for developing Indigenous community-based monitoring: Examples from the Canadian oil sands region
Bibliographic record
Abstract
Abstract Historically, environmental research and monitoring in the Alberta oil sands region (OSR) located in northeastern Alberta, Canada, have largely neglected, meaningful Indigenous participation. Through years of experience on the land, Indigenous knowledge (IK) holders recognize change on the landscape, drawing on inextricable links between environmental health and practicing traditional rights. The cumulative impacts of crude oil production are of great concern to Indigenous communities, and monitoring initiatives in the OSR provide unique opportunities to develop Indigenous community-based monitoring (ICBM). A review of ICBM literature on the OSR from 2009 to 2020 was completed. Based on this review, we identify best practices in ICBM and propose governance structures and a framework to support meaningful integration of ICBM into regulatory environmental monitoring. Because it involves multimedia monitoring and produces data and insights that integrate many aspects of the environment, ICBM is important for natural science research. ICBM can enhance the relevance of environmental monitoring by examining relationships between physical and chemical stressors and culturally relevant indicators, so improving predictions of long-term changes in the environment. Unfortunately, many Indigenous communities distrust researchers owing to previous experiences of exploitive use of IK. In the present paper, we recommend important practices for the integration of IK into regional environmental monitoring programs. ICBM is important to communities because it includes conditions to which communities can exercise traditional rights, and highlight how industrial activities affect this ability. Equally important, ICBM can generate a resurgence of Indigenous languages and subsequently traditional practices; it can also revive the connection with traditional lands and improve food security. Integr Environ Assess Manag 2022;18:407-427. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). KEY POINTS The paper provides a unique way of organizing the integration of Indigenous knowledge (IK) and Western science (WS) using a conceptual model, which can allow regional monitoring programs to constantly evaluate research objectives and identify gaps. It is not the intention of this paper to adapt IK or WS to any model or monitoring program, but to discuss the integrative ability of both to better understand pressure/stressor-pathways and response relationships of environmental impacts in the oil sands region. Contextualizing each program into the conceptual model is useful for large monitoring programs, such as the Oil Sands Monitoring (OSM) program, to integrate large amounts of data assessing different aspects of the environment over time and space. Indigenous community-based monitoring approaches, such as those led by the Mikisew Cree and Athabasca Chipewyan First Nations, support regional monitoring where data are easily captured in regional-scale models.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".