Bibliographic record
Abstract
The Lafitte Greenway is a 3.1 mile linear park of 65 acres (26 hectares) running from New Orleans' famous French Quarter through nine of the city's most historic neighborhoods.In addition to the greenway design, the project involved the creation of a revitalization plan for the adjoining neighborhoods and an operation and management plan for the greenway.A multi-disciplinary team, led by landscape architects included architects, civil engineers, ecologists, economists, as well as, experts in park management and operations and crime prevention through environmental design.An extensive public engagement process was also utilized.The design methodology employed an evidence-driven approach considering over thirty categories of metrics embracing issues of environment, community, economics, and art.The project was benchmarked against the standards of LEED and Sustainable Sites but goes far beyond these frameworks to establish a new standard for sustainable design.Factors considered include: stormwater management, urban heat island, urban wildlife, native plant use, recycled content, public health, employment, tax generation, housing values, crime rates, and safe routes to school.The Lafitte Greenway and Revitalization Plans illustrate the benefits and challenges of a holistic approach to planning and design with lessons for future projects of all scales.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".