Preserving Mobile Home Communities through Shared-Equity Ownership Mechanisms: A Case Study of the Burnsville Land Community (BLC)
Bibliographic record
Abstract
As sprawl and an increase of new residents in many rural areas in Western North Carolina (WNC) lead to increased land values, the owners of many mobile home communities (MHCs) are selling the land for development, resulting in the displacement of tenants. In some areas of the U.S. residents of MHCs have formed models of social ownership of the land on which their homes are located to prevent such displacement. This case study traces the events leading up to and surrounding the establishment of the Burnsville Land Community (BLC), the result of the first such effort in North Carolina. Initiated in 2007 by a group of predominantly Mexican families, residents were assisted by a number of non-profit organizations from outside the community. In describing the events leading up to and surrounding the establishment of the BLC the authors seek to meet three research objectives: a) Shed light on the emerging and under-researched phenomenon of predominantly Latino mobile home communities in the mountains of Southern/Central Appalachia; b) Consider the efficacy of social models of home ownership in preventing displacement of mobile home residents in this region; and c) Explore similarities between development of Latino MHCs in Appalachia and colonia housing developments along the U.S./Mexico border region. We do so for the purpose of determining whether lessons learned from the colonia experience could have been, or might still be, useful to those concerned with displacement of residents in predominantly Latino MHCs in Southern/Central Appalachia or elsewhere.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".