Bibliographic record
Abstract
There have been continuous efforts to introduce policies and measures for revitalizing local businesses and industries which became obsolete physically and economically in downtown areas. Those strategies can play a significant role for leveraging local economic growth as well as improving environmental quality of the areas. In particular, the consistency of the residents’voluntary participation and the public support made it possible to achieve local economic development and cultural and community revitalization in downtown areas of developed countries. Among a variety of relevant endeavors, BID (Business Improvement District) is considered as one of the most important measures which has become popular in the U.S., the U.K., Germany and Canada. This study introduces and compares some BIDs and similar measures which have been implemented in the U.S., the U.K. and Japan. Then, it investigates major issues related to backgrounds, purposes and specific contents of the strategies when they are put into effect. The purpose of this research is to suggest some implications for introducing innovative urban policies and measures for regenerating depressed urban areas and stagnant downtown areas physically and economically. They can include grass-roots organization and self-sustaining financing strategies through the partnership among local residents, municipalities and central authorities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".