History, overview, and governance of environmental monitoring in the oil sands region of Alberta, Canada
Bibliographic record
Abstract
Abstract Over the past decades, concerns regarding the local and cumulative impacts of oil sands development have been increasing. These concerns reflect the industry's emissions, land disturbance, water use, and the resulting impacts to Indigenous Rights. Effective environmental management is essential to address and ultimately manage these concerns. A series of ambient regional monitoring programs in the oil sands region (OSR) have struggled with scope and governance. In the last 10 years, monitoring has evolved from a regulatory-driven exercise implemented by industry into a focused, collaborative, multistakeholder program that attempts to integrate rigorous science from a multitude of disciplines and ways of knowing. Monitoring in the region continues to grapple with leadership, governance, data management, scope, and effective analysis and reporting. This special series, “A Decade of Research and Monitoring in the Oil Sands Region of Alberta, Canada,” provides a series of critical reviews that synthesize 10 years of published monitoring results to identify patterns of consistent ecological responses or effects, significant gaps in knowledge, and recommendations for improved monitoring, assessment, and management of the region. The special series considered over 300 peer-reviewed papers and represents the first integrated critical review of the published literature from the region. This introductory paper of the series introduces the history of ambient environmental monitoring in the OSR and discusses historic and ongoing challenges with the environmental monitoring effort. While significant progress has been made in areas of governance, expanded geographical scope, and inclusion of Indigenous communities in monitoring in the region, significant issues remain regarding a lack of integrated reporting on environmental conditions, public access to data, and continuity of monitoring efforts over time. Integr Environ Assess Manag 2022;18:319–332. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). KEY POINTS This article introduces a special series that reviews over 300 manuscripts published over 10 years across environmental disciplines in the oil sands region of Alberta. The series is the first integrated critical review of published literature in the region. We discuss the history of ambient environmental monitoring in the region and the historic and ongoing challenges including how western science and Indigenous knowledge have been considered. While some progress has been made, significant issues remain regarding a lack of integrated reporting on environmental conditions, lack of public access to data, and discontinuity of monitoring efforts over time due, in part, to political influence.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.017 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".