Strategic environmental assessment and land use planning: An international evaluation
Bibliographic record
Abstract
Strategic Environmental Assessment and Land Use Planning covers not only how much such SEAs are carried out and in what context, but whether they are effective and why. It provides invaluable insights for practitioners and researchers in this rapidy evolving field' Riki Therivel, author of Strategic Environmental Assessment in Action Strategic Environmental Assessment and Land Use Planning provides an authoritative, international evaluation of the SEA of land use plans. The editors place the SEA of land use plans in context, and uniquely qualified contributors then evaluate systems in Canada, Denmark, Germany, Hong Kong, Hungary, Ireland, The Netherlands, New Zealand, Portugal, South Africa, Sweden, the United Kingdom, the United States and the World Bank. These chapters provide a description of the context in each country, a case study of the use of SEA in land use planning and an evaluation of each SEA system against a set of generic criteria specially designed to anlayse different aspects of SEA. The contributors critically review each SEA system, SEA process and SEA outcome, and conclude by summarizing their findings. The editors draw the various national perspectives together in a final chapter and derive widely applicable conclusions about SEA and land use planning. This book is a core text for all students in environmental assessment, land use planning, environmental science, environmental management, development studies, geography, landscape design and law and engineering. It is also essential reading for all governments and environmental regulators, academics, researchers and environmental and planning consultants worldwide who are involvedin SEA research, practice and training.
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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 | 0.044 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".