A Framework for Analyzing Nonprofit Governance and Accountability Policies and Strategies

This paper presents a framework for analyzing the sprawling topic of nonprofit governance and accountability. It distinguishes various accountability-generating mechanisms and actors, including the unit-level governing board; government policies aimed at shaping the behavior of governing boards; and a broader, natural demand for accountability, generated by an organizations many stakeholders. The aims of these accountability mechanisms and actors also vary, and include the prevention of theft and fraud; the efficient use of resources; the choice of socially valuable goals; and the effective performance of an organization in service of those goals.This publication is Hauser Center Working Paper No. 33.3. Hauser Working Paper Series Nos. 33.1-33.9 were prepared as background papers for the Nonprofit Governance and Accountability Symposium October 3-4, 2006

High energy scattering

Imperial Users onl

Effects of high temperature and pressure in the production of near-ideal graphite

Imperial Users onl

Historical Archaeology in Texas: A Bibliography

Documented in this bibliography are the varied sources in which information concerning historical archaeology in Texas has appeared. In all, 509 references are cross-referenced in this monograph with author, subject, and county. Much of the state is represented with subjects relating to 163 of the 254 Texas counties

A System for Accessible Artificial Intelligence

While artificial intelligence (AI) has become widespread, many commercial AI systems are not yet accessible to individual researchers nor the general public due to the deep knowledge of the systems required to use them. We believe that AI has matured to the point where it should be an accessible technology for everyone. We present an ongoing project whose ultimate goal is to deliver an open source, user-friendly AI system that is specialized for machine learning analysis of complex data in the biomedical and health care domains. We discuss how genetic programming can aid in this endeavor, and highlight specific examples where genetic programming has automated machine learning analyses in previous projects.Comment: 14 pages, 5 figures, submitted to Genetic Programming Theory and Practice 2017 worksho