The Simple Analytics of Accountability

In this paper, the author offers a schematic that distinguishes the actors, interactions, and dynamics of various accountability relationships. A number of distinctions including those between responsibility and accountability, moral and legal accountability claims, and socially or governmentally generated demand for accountability are offered to assist those working on accountability policies or strategies and who may be struggling with generic conceptions of accountability that conflate all of these elements. This publication is Hauser Center Working Paper No. 33.9. 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

The Public Value Scorecard: A Rejoinder and an Alternative to "Strategic Performance Measurement and Management in Non-Profit Organizations"

Robert Kaplan's Balanced Scorecard has played an important and welcome role in the nonprofit world as nonprofit organizations have struggled to measure their performance. Many nonprofit organizations have taken both general inspiration and specific operational guidance from the ideas advanced in this important work. Their pioneering efforts to apply these concepts to their own particular settings have added a layer of richness to the important concepts. Given the great contribution of this work to helping nonprofits meet the challenge of measuring their performance, it seems both ungracious and unhelpful to criticize it. Yet, as I review the concepts of the Balanced Scorecard, and look closely at the cases of organizations that have tried to use these concepts to measure their performance, I believe that some systematic confusions arise. Further, I think the source of these confusions lies in the fact the basic concepts of the Balanced Scorecard have not been sufficiently adapted from the private, for-profit world where they were born to the world of the nonprofit manager where they are now being applied. Finally, I think a different way of thinking about nonprofit strategy and linking that to performance measurement exists that is simpler that and more reliable for nonprofit organizations to rely upon. The purpose of this paper is to set out these contrarian ideas. This publication is Hauser Center Working Paper No. 18. The Hauser Center Working Paper Series was launched during the summer of 2000. The Series enables the Hauser Center to share with a broad audience important works-in-progress written by Hauser Center scholars and researchers

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

Globalization, NGOs and Multi-Sectoral Relations

This paper seeks to make sense of the impact of globalization on nonprofit, nongovernmental organizations. We argue that globalization processes have contributed to the rising numbers and influence of NGOs in many countries, and particularly in the international arena. International NGOs and NGO alliances are emerging as increasingly influential players in international decision-making, and we discuss some of the roles they can be expected to play in the future. We consider whether the emergence of domestic and international NGOs as important policy makers strengthens or weakens the future of democratic accountability, and we suggest several patterns of interaction among civil society, government and business in future governance issues.This publication is Hauser Center Working Paper No. 1. The Hauser Center Working Paper Series was launched during the summer of 2000. The Series enables the Hauser Center to share with a broad audience important works-in-progress written by Hauser Center scholars and researchers

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org

Transformational Autonomy and Personal Transportation: Synergies and Differences Between Cars and Planes

Highly automated cars have undergone tremendous investment and progress over the past ten years with speculation about fully-driverless cars within the foreseeable, or even near future, becoming common. If a driverless future is realized, what might be the impact on personal aviation? Would self-piloting airplanes be a relatively simple spin-off, possibly making travel by personal aircraft also commonplace? What if the technology for completely removing human drivers turns out to be further in the future rather than sooner; would such a delay suggest that transformational personal aviation is also somewhere over the horizon or can transformation be achieved with less than full automation? This paper presents a preliminary exploration of these questions by comparing the operational, functional, and implementation requirements and constraints of cars and small aircraft for on-demand mobility. In general, we predict that the mission management and perception requirements of self-piloting aircraft differ significantly from self-driving cars and requires the development of aviation specific technologies. We also predict that the highly-reliable control and system automation technology developed for conditionally and highly automated cars can have a significant beneficial effect on personal aviation, even if full automation is not immediately feasible

Comparative Genomic Hybridization Array Analysis

At the present time, there is increasing evidence that cancer may be regulated by the number of copies of genes in tumor cells. Through microarray technology it is now possible to measure the number of copies of thousands of genes and gene segments in samples of chromosomal DNA. Microarray comparative genomic hybridization (array CGH) provides the opportunity to both measure DNA sequence copy number gains and losses and map these aberrations to the genomic sequence. Gains can signify the over-expression of oncogenes, genes which stimulate cell growth and have become hyperactive, while losses can signify under-expression of tumor suppressor genes, genes whose activity stops the formation of tumors. In order to better understand the progression of cancer and the differences between cancer and non-cancer tissue it is of great importance to fully understand what is happening at the chromosomal level. In the hopes of finding a genetic signature for subtypes of cancer, it is our intention to explore statistical approaches to array CGH data. The Waldman Lab at UCSF-CCC graciously allowed us to access data from their renal cancer study. This project was designed to determine whether microarray information on copy number of genes could be used to discriminate among four subtypes of renal cancer

Accountability, Strategy, and International Non-Governmental Organizations

Increased prominence and greater influence expose international non-governmental development and environmental organizations (INGOs) to increased demands for accountability from a wide variety of stakeholdersdonors, beneficiaries, staffs, and partners among others. This paper focuses on developing the concept of INGO accountability, first as an abstract concept and then as a strategic idea with very different implications for different INGO strategies. We examine those implications for INGOs that emphasize service delivery, capacity-building, and policy influence. We propose that INGOs committed to service delivery may owe more accountability to donors and service regulators; capacity-building INGOs may be particularly obligated to clients whose capacities are being enhanced; and policy influence INGOs may be especially accountable to political constituencies and to influence targets. INGOs that are expanding their activities to include new initiatives may need to reorganize their accountability systems to implement their strategies effectively. This publication is Hauser Center Working Paper No. 7. The Hauser Center Working Paper Series was launched during the summer of 2000. The Series enables the Hauser Center to share with a broad audience important works-in-progress written by Hauser Center scholars and researchers

Survival Point Estimate Prediction in Matched and Non-Matched Case-Control Subsample Designed Studies

Providing information about the risk of disease and clinical factors that may increase or decrease a patient\u27s risk of disease is standard medical practice. Although case-control studies can provide evidence of strong associations between diseases and risk factors, clinicians need to be able to communicate to patients the age-specific risks of disease over a defined time interval for a set of risk factors. An estimate of absolute risk cannot be determined from case-control studies because cases are generally chosen from a population whose size is not known (necessary for calculation of absolute risk) and where duration of follow-up is not known (necessary for calculation of incidence). This problem can sometimes be overcome by using a nested case-control design. We have collected data on a National Cancer Institute funded population-based cohort study. This study contains a matched set of cases and controls within the cohort. This design is more cost-efficient than a full cohort study since expensive predictor variables (genomic measures, sex hormone levels, mammographic breast density) are measured on all of the cases, but on only a sample of the cohort who did not develop the outcome of interest (the controls). In addition, this design avoids the potential biases of conventional case-control studies that draw cases and controls from different populations. Importantly, the presence or absence of the outcome of interest has been established for the entire cohort within the same time period. The specifics of the sampling in our study do not adhere to the assumptions for absolute risk estimation methods previously developed in the literature. Here we introduce a novel method which provides locally efficient estimators to predict the absolute risk of a cohort from measures only taken on the matched case-control participants. The proposed method is evaluated using simulation studies and survival data from women with ductal carcinoma in situ, a non-invasive form of breast cancer. A generalization of the proposed method is related to other similar sampling designs such as nested case-control, case-cohort, and two-stage case-control