Identifying Priority Areas for Wetlands Restoration along the Louisiana Coast under the Coastal Wetlands Planning, Protection, and Restoration Act of 1990
Bibliographic record
Abstract
This research uses a sequence of hedonic spatial regressions across successively larger ranges of contiguous census‐block groups (CBGs) to identify priority areas for wetlands restoration along the Louisiana coast under the Coastal Wetlands Planning, Protection, and Restoration Act (CWPPRA). Marginal implicit prices of wetlands and open water from the regressions were translated into amenity values received by single‐family house owners within five Queen orders of CBGs. Differences between amenity values of wetlands and open water were used to proxy the amenity values of four potential restoration sites. These differences were summed over housing locations within each order of contiguous GBG neighbors and across the orders for each site. Based on the aggregate amenity value per acre from wetlands restoration and under the assumption that most restoration projects are designed to benefit as wide an area as possible, the priority ranking for restoration becomes: (1) Fresh Bayou, (2) Sabine National Wildlife Refuge, (3) Bayou LaBranchee, and (4) Barataria Bay Waterway. Dans le présent article nous avons utilisé une séquence de régressions spatiales hédoniques dans de larges groupes d'îlots de recensement contigus pour déterminer les secteurs prioritaires pour la restauration des milieux humides le long de la côte de la Louisiane en vertu de la Coastal Wetlands Planning, Protection, and Restoration Act (CWPPRA). Les prix marginaux implicites des milieux humides et des zones d'eau libre obtenus à partir des régressions ont été traduits en valeurs d'agrément formulées par les propriétaires de maisons unifamiliales dans cinq regroupements d'îlots de recensement contigus. Les différences entre les valeurs d'agrément des milieux humides et des zones d'eau libre ont été utilisées pour donner une approximation des valeurs d'agrément de quatre sites de restauration potentiels. Ces différences ont été totalisées pour chaque résidence dans chacun des regroupements et entre les regroupements pour chaque site. D'après la valeur d'agrément agrégée par acre de restauration des milieux humides et l'hypothèse voulant que la plupart des projets de restauration soient conçus pour profiter à la plus grande zone possible, l'ordre de priorité pour la restauration est la suivante: 1. Fresh Bayou; 2. Sabine National Wildlife Refuge; 3. Bayou LaBranchee; 4. Barataria Bay Waterway.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".