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Record W2296901068

Preserving Mobile Home Communities through Shared-Equity Ownership Mechanisms: A Case Study of the Burnsville Land Community (BLC)

2013· article· en· W2296901068 on OpenAlexvenueno aff
Terence M. Milstead, John D. Post, Rosie Tighe

Bibliographic record

VenueJournal of rural and community development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAppalachiaUrban sprawlEquity (law)Land tenureGeographyEconomic growthLand ValuesSocioeconomicsGentrificationPolitical scienceBusinessLand useSociologyAgricultureArchaeologyEcologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.101
GPT teacher head0.323
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2013
Admission routes1
Has abstractyes

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