The reasons for and against composite indicators are briefly reviewed, as well as the available theories for their construction. After noting the strong normative dimension of these measures—which ultimately aim to ‘tell a story’, e.g. to promote the social discovery of a particular phenomenon, we inquire whether a less partisan use of a composite indicator can be proposed by allowing more latitude in the framing of its construction. We thus explore whether a composite indicator can be built to tell ‘more than one story’ and test this in practical contexts. These include measures used in convergence analysis in the field of cohesion policies and a recent case involving the World Bank’s Doing Business Index. Our experiments are built to imagine different constituencies and stakeholders who agree on the use of evidence and of statistical information while differing on the interpretation of what is relevant and vital.
In this article, we examine the kinds of control practices that emerge with the introduction of digital technologies, and how these technologies are employed to shape power within workplaces. We present a comparative conceptual review of work practices by contrasting remote work and the use of workplace wearables. We trace forms of power and control that have been enacted with the adoption of these work‐related technologies and associated practices. We find that the prevailing literature focuses on the practices enacted by management in order to control workers and exert power over them, and we propose that a more comprehensive approach be taken. In support of this view, we show how the concept of appropriation emerges from science and technology studies, and we argue that such a concept would be useful for exploring how workers use and incorporate digital technologies into their daily lives, thus reshaping power in organizations. 相似文献
Motivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distribution of a single event time with semicompeting-risks data. We conduct both asymptotics and simulation studies to examine the proposed approach in consistency, efficiency, and robustness. Data from the breast cancer program are employed to illustrate this research.
