Coffee and Politics in Central America

http://deepblue.lib.umich.edu/bitstream/2027.42/51098/1/330.pd

Cotton and Revolution in Nicaragua

http://deepblue.lib.umich.edu/bitstream/2027.42/51087/1/319.pd

Intimacy, Identity and Dignity: Human Needs and the Primacy of Production in Marxist Social Thought

http://deepblue.lib.umich.edu/bitstream/2027.42/51268/1/502.pd

Revolution and the Agrarian Bourgeoisie in Nicaragua

Also CSST Working Paper #8.http://deepblue.lib.umich.edu/bitstream/2027.42/51131/1/363.pd

The Social Origins of Dictatorship, Democracy, and Socialist Revolution in Central America

Also CSST Working Paper #35.http://deepblue.lib.umich.edu/bitstream/2027.42/51172/1/405.pd

Coffee, Copper, and Class Conflict in Central America and Chile: A Critique of Zeitlin's Civil Wars in Chile and Zeitlin and Ratcliff's Landlords and Capitalists

Also CSST Working Paper #3.http://deepblue.lib.umich.edu/bitstream/2027.42/51115/1/347.pd

Social theory and peasant revolution in Vietnam and Guatemala

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43640/1/11186_2004_Article_BF00912078.pd

Program in Comparative Study of Social Transformations

Also CSST Working Paper #1.http://deepblue.lib.umich.edu/bitstream/2027.42/51112/1/344.pd

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building