Bibliographic record
Abstract
Hurricane Katrina displaced many New Orleans residents, leaving in its wake tens of thousands of vacant lots and buildings. In 2010, estimates show that over 57,000 properties lay empty in the city, especially in the poorer neighborhoods. These properties are not contributing to the fabric of the city; in most places, they are a sign of defeat, an eyesore, or a haven for crime. The neighborhood of St. Roch is experiencing the negative effects of these properties day in and day out and from year to year. Almost a quarter of the lots are vacant in the St. Roch neighborhood, leading to crime and creating a nuisance and a blemish on the community. Coupled with the lack of ownership there is an ailing stormwater management infrastructure leading to areas of fl ooding after routine storms. In addition to these concerns, there is a lack of fresh, inexpensive and accessible food throughout the area. Although St. Roch’s vacant lots have a negative effect on the community, they present a tremendous opportunity. Their dispersal around the neighborhood presents the opportunity to connect them to churches, schools, retail outlets, as well as providing other uses and services to the neighborhood. The thoughtful design of these locations will demonstrate a site-sensitive approach to the local ecology, culture, and economy of the neighborhood. Such design includes the community throughout the entire
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.801 | 0.701 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".