CHARACTERIZING PROJECT AND STRATEGIC APPROACHES TO REGIONAL CUMULATIVE EFFECTS ASSESSMENT IN CANADA
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
Advancing cumulative effects assessments (CEA) to the regional scale, spatially and strategically, has been well argued but slow to evolve. Part of the problem is that "regional" CEA is a flexible concept, varying considerably in form and function from the project to the more strategic levels. This paper steps back from current discussions of assessment frameworks and methodologies to present a typology of regional approaches to CEA based on its multiple characteristics, functions, and expectations. Drawing upon current literature and interviews with international practitioners, we conceptualize regional CEA from two broad perspectives: EIA-driven approaches and SEA-driven approaches, illustrated with Canadian case examples. Each approach to CEA has its own merits that make it suitable to address particular types of cumulative problems at different tiers of assessment, and each of which can be expected to deliver different types of assessment results. The failure to fully recognize this "one concept–multiple form" characteristic is, in part, why the EA community has struggled in developing supportive methodological and institutional frameworks for regional CEA. We demonstrate that many of the disappointments with CEA are not the result of EIA-driven applications per se, but rather the result of mismatched CEA frameworks and expectations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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