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Record W2048606445 · doi:10.1526/003601108785766525

Poverty Catchments: Migration, Residential Mobility, and Population Turnover in Impoverished Rural Illinois Communities

2008· article· en· W2048606445 on OpenAlex
Matt Foulkes, K. Bruce Newbold

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRural Sociology · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPovertyDestinationsRural areaPopulationRural povertyGeographySocioeconomicsEconomic growthDevelopment economicsRural populationRural sociologyAgricultureRural developmentPolitical scienceSociologyEconomicsDemographyTourism

Abstract

fetched live from OpenAlex

Abstract Research has thoroughly documented how out‐migration of the educated and skilled from rural areas leaves behind a poorer population and creates pockets of rural poverty. Recently, studies have recognized that the poor are also geographically mobile and that poverty migration patterns can reinforce rural poverty concentrations. In this process, certain impoverished rural communities in economically depressed regions receive a disproportionate share of poverty migrants, concentrating poverty in certain locations. This paper examines the conditions and processes through which poor rural communities become likely destinations for a highly mobile segment of the rural poor and near‐poor. Utilizing case studies of depressed rural Illinois communities, it investigates how the interplay of community factors and the behavior of migrants transforms rural communities from residentially stable to highly mobile, impoverished places.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.297
Teacher spread0.271 · 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