Selection of valued ecosystem components in cumulative effects assessment: lessons from Canadian road construction projects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Valued ecosystem component (VEC) selection is a core component of cumulative effects assessment (CEA) and gives direction to impact analysis, mitigation and monitoring. Yet little is known about CEA VEC selection practices. This paper examines 11 Canadian road infrastructure project CEAs completed between 1995 and 2011 to determine how VEC selection in CEA is performed, and whether these practices are sensitive to the linear project development context. Document review and semi-structured interviews reveal an absence of VEC selection guidance, late timing of cumulative effects considerations in impact assessment, lack of sensitivity in CEA VEC selection to the unique, linear nature of the road construction projects and a general lack of insightful, creative approaches to CEA VEC selection – ones that better reflect potential impacts to social and economic aspects of the environment – despite it being shown to be a values-driven, subjective process. There is a clear need for regional databases to support consistent CEA VEC selection processes, and the development of CEA-specific VEC selection guidance.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it