Retrofitting Drucker: Knowledge work under cognitive capitalism

This article uses Peter Drucker's work vector-like, to carry the thesis of cognitive capitalism into the management field. Drucker's prophetic insights into the knowledge society are juxtaposed with recent, Italian autonomist Marxist-inspired analyses of capitalism's cognitive phase. If the capacity to create knowledge – or what autonomists call the ‘general intellect’ – is becoming the key productive force, arguably there is a need for a full-blown social form of knowledge management. Our reading of Drucker thus retrieves the one worthwhile thing from the rubble of normative knowledge management. It is the idea of society-level knowledge management premised on a universal and unconditional guaranteed basic income (GBI; or social wage). Basic income represents not just a social investment in knowledge, which Drucker himself called for, but also compensation for biolabour's augmented social productivity. With Drucker as the steppingstone, we conclude, the autonomist tradition merits greater attention from critical management and organisational scholars interested in factoring class and gender back into the knowledge management equation.     

Critical Realism,Dialectics, and Qualitative Research Methods

Critical realism has been an important advance in social science methodology because it develops a qualitative theory of causality which avoids some of the pitfalls of empiricist theories of causality. But while there has been ample work exploring the relationship between critical realism and qualitative research methods there has been noticeably less work exploring the relationship between dialectical critical realism and qualitative research methods. This seems strange especially since the founder of the philosophy of critical realism, Roy Bhaskar, employs and develops a range of dialectical concepts in his later work in order to extend the main tenets of critical realism. The aim of this paper is to draw on Bhaskar's later work, as well as Marxism, to reorient a critical realist methodology towards a dialectical approach for qualitative research. In particular, the paper demonstrates how dialectical critical realism can begin to provide answers to three common criticisms made against original critical realist methodology: that the qualitative theory of causal powers and structures developed by critical realists is problematic; that critical realist methodology contains values which prove damaging to empirical research; and that critical realists often have difficulties in researching everyday qualitative dilemmas that people face in their daily lives.     

Generalizing the standardized hazard ratio to multivariate proportional hazards regression,with an application to clinical~genomic studies

The standardized hazard ratio for univariate proportional hazards regression is generalized as a scalar to multivariate proportional hazards regression. Estimators of the standardized log hazard ratio are developed, with corrections for bias and for regression to the mean in high-dimensional analyses. Tests of point and interval null hypotheses and confidence intervals are constructed. Cohort sampling study designs, commonly used in prospective–retrospective clinical genomic studies, are accommodated.     

Q-LEARNING WITH CENSORED DATA

We develop methodology for a multistage-decision problem with flexible number of stages in which the rewards are survival times that are subject to censoring. We present a novel Q-learning algorithm that is adjusted for censored data and allows a flexible number of stages. We provide finite sample bounds on the generalization error of the policy learned by the algorithm, and show that when the optimal Q-function belongs to the approximation space, the expected survival time for policies obtained by the algorithm converges to that of the optimal policy. We simulate a multistage clinical trial with flexible number of stages and apply the proposed censored-Q-learning algorithm to find individualized treatment regimens. The methodology presented in this paper has implications in the design of personalized medicine trials in cancer and in other life-threatening diseases.     

Inheritance,poverty, and disability

Inheritance is a significant means of transferring wealth from one generation to the next, and therefore increasingly attracts attention from researchers and policy-makers working on intergenerational and multidimensional poverty. However, until now disabled persons have been overlooked in these discussions. This oversight is particularly unfortunate because, as a group, the estimated one billion people with disabilities (some 15% of the world’s population) are among the poorest and most marginalized of the global population. Over the past decade, a small but growing literature has examined the recursive connections between poverty and disability throughout the developing world. In this paper, we argue that disabled individuals are routinely denied inheritance rights in many low-income and middle-income countries, and that this is a significant and largely unrecognized contributor to their indigence. The denial of inheritance is both a social justice issue and a practice that can no longer be overlooked if disabled persons are to be brought into the development mainstream.     

Digital Finance and FinTech: current research and future research directions

Since decades, the financial industry has experienced a continuous evolution in service delivery due to digitalization. This evolution is characterized by expanded connectivity and enhanced speed of information processing both at the customer interface and in back-office processes. Recently, there has been a shift in the focus of digitalization from improving the delivery of traditional tasks to introducing fundamentally new business opportunities and models for financial service companies. Digital Finance encompasses a magnitude of new financial products, financial businesses, finance-related software, and novel forms of customer communication and interaction—delivered by FinTech companies and innovative financial service providers. Against this backdrop, the research on finance and information systems has started to analyze these changes and the impact of digital progress on the financial sector. Therefore, this article reviews the current state of research in Digital Finance that deals with these novel and innovative business functions. Moreover, it gives an outlook on potential future research directions. As a conceptual basis for reviewing this field, the Digital Finance Cube, which embraces three key dimensions of Digital Finance and FinTech, i.e., the respective business functions, the technologies and technological concepts applied as well as the institutions concerned, is introduced. This conceptualization supports researchers and practitioners when orientating in the field of Digital Finance, allows for the arrangement of academic research relatively to each other, and enables for the revelation of the gaps in research.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

The heritability of emergent leadership: Age and gender as moderating factors

In this study, we examined the moderating influences of gender and age with respect to testing the heritability of leadership emergence. A large data base of 12,112 twins from Sweden was used in the current study to decompose the variance of emergent leadership into an unobservable genetic component and environmental components that are either common or unshared among twin pairs. Consistent with prior leadership research on genetics, we found that a genetic factor is able to explain a significant proportion of the variation across individuals in predicting how twins perceive their emergent leadership behavior (about 44% for women and 37% for men). Furthermore, we also found that the magnitude of genetic influence on emergent leadership varied with age, but only for women with the heritability estimate being highest for the mid-age women versus lowest for the older women. Implications for advancing research on the genetic and environmental influences on leadership emergence are discussed.