Identifying Opportunities for the Revitalization of Downtown Bloomsburg
Bibliographic record
Abstract
American downtowns were once the place to see and be seen, but the introduction of the shopping mall in the late 1950s challenged this notion and gave the American consumer a different place to spend their time and money. The prevalence of shopping malls has slowly been declining across the country since the beginning of this century, leaving room in the American retail landscape for downtowns to reclaim their status as community and retail centers. Towns across the U.S. are turning to national and local organizations to assist them in revitalizing their downtown districts. Downtown Bloomsburg, Inc. (DBI), a non-profit organization located in the small town of Bloomsburg, Pennsylvania, has been working since 2006 to revitalize its town’s downtown and main street area. The unique findings presented here were derived from a four month long ethnographic study of downtown Bloomsburg merchants and shoppers and are meant to be used by DBI as a supplemental guide for further revitalization of the town.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".