Once treated as the absence of knowledge, ignorance today has become a highly influential topic in its own right, commanding growing attention across the natural and social sciences where a wide range of scholars have begun to explore the social life and political issues involved in the distribution and strategic use of not knowing. The field is growing fast and this handbook reflects this interdisciplinary field of study by drawing contributions from economics, sociology, history, philosophy, cultural studies, area studies, anthropology, (...) legal studies, feminist studies, and related fields in order to serve as a seminal guide to the political, legal and social uses of ignorance in social and political life. (shrink)

"This volume emerged from workshops held at Pennsylvania State University in 2003 and Stanford University in 2005"--P. vii.

In this book Bruno Latour brings together these different approaches to provide a lively and challenging analysis of science, demonstrating how social context..

In A Social History of Truth, Shapin engages these universal questions through an elegant recreation of a crucial period in the history of early modern science: ...

Despite all the attention to Big Data and the claims that it represents a “paradigm shift” in science, we lack understanding about what are the qualities of Big Data that may contribute to this revolutionary impact. In this paper, we look beyond the quantitative aspects of Big Data and examine it from a sociotechnical perspective. We argue that a key factor that distinguishes “Big Data” from “lots of data” lies in changes to the traditional, well-established “control zones” that facilitated clear (...) provenance of scientific data, thereby ensuring data integrity and providing the foundation for credible science. The breakdown of these control zones is a consequence of the manner in which our network technology and culture enable and encourage open, anonymous sharing of information, participation regardless of expertise, and collaboration across geographic, disciplinary, and institutional barriers. We are left with the conundrum—how to reap the benefits of Big Data while re-creating a trust fabric and an accountable chain of responsibility that make credible science possible. (shrink)