James R. Hull

ORCID: 0000-0002-1799-8204
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About
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Research Areas
  • Income, Poverty, and Inequality
  • Poverty, Education, and Child Welfare
  • Agricultural risk and resilience
  • Conservation, Biodiversity, and Resource Management
  • Migration and Labor Dynamics
  • Southeast Asian Sociopolitical Studies
  • Sentiment Analysis and Opinion Mining
  • Social and Economic Development in India
  • Authorship Attribution and Profiling
  • China's Socioeconomic Reforms and Governance
  • Economic and Environmental Valuation
  • Migration, Ethnicity, and Economy
  • Economic and Social Development
  • Indigenous Cultures and Socio-Education
  • Personality Traits and Psychology
  • Economic Theory and Policy
  • Social Sciences and Policies
  • Land Use and Ecosystem Services
  • Land Rights and Reforms

University of Maryland, College Park
2021

Brown University
2013

University of California, Irvine
2011-2013

University of California System
2013

University of North Carolina at Chapel Hill
2007

Obtaining the labor necessary to perform household agricultural tasks in contexts with periods of intense demand can be a challenge. The challenge is especially pronounced Northeast Thailand where biophysical conditions constrain possibilities for reduction, while still maintaining productivity, and demographic changes supply laborers place some households particular bind. Out-migration hypothesized impact household's decision grow rice method acquiring labor. influences these decisions...

10.1177/011719680701600402 article EN Asian and Pacific migration journal 2007-12-01

In this paper the theoretical tradition of coping strategies and capital portfolios is used as basis for adaption combination existing methodologies to analyze well-being in rural households. Special attention given comparisons among different contexts. First we estimate a multidimensional measurement poverty based on fuzzy logic two areas frontiers: Nang Rong, Thailand, Altamira, Amazon Basin Brazil. To enable cross-contextual comparison calculated second using subset shared measurements...

10.1590/s0102-30982013000100013 article EN cc-by-nc Revista Brasileira de Estudos de População 2013-06-01

Feature engineering is an important step in classical NLP pipelines, but machine learning engineers may not be aware of the signals to look for when processing foreign language text.The Russian Extraction Toolkit (RFET) a collection feature extraction libraries bundled ease use by who do speak Russian.RFET's current set includes features applicable social media genres text and computational science tasks.We demonstrate effectiveness tool using it personality trait identification task.We...

10.26615/978-954-452-072-4_066 article EN 2021-01-01
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