Is scientific knowledge socially constructed? A Bayesian account of Laboratory Life.

In the book Laboratory Life Latour and Woolgar present an account of how scientific "facts" are formed through a process of microsocial interactions among individuals and "inscription devices" in the lab initially described as social construction. The process moves through a series of steps during which the details and nature of the object become more and more certain until all qualifications are dropped, and the "fact" emerges as secure scientific knowledge. An alternative to this account is described based on a Bayesian probabilistic framework which arrives at the same end point. The motive force for the constructivist approach appears to involve social processes of convincing colleagues while the Bayesian approach relies on the consistency of theory and evidence as judged by the participants. The role of social processes is discussed in Bayesian terms, the acquisition and asymmetry of information, and its analogy to puzzle solving. Some parallels between the Bayesian and constructivist accounts are noted especially in relation to information theory.

Quantification of knowledge content of a high impact innovation: recombinant DNA.

Quantitative analysis of knowledge content of a significant technological innovation is a novel approach to understand the scientific discovery process. Here we describe such an analysis applied to the invention of recombinant DNA technology in the early 1970's. Two focal papers are selected, i.e., Jackson et al., 1972 and Cohen et al., 1973. A knowledge framework called EApc is described to categorize knowledge types and their quantification. The focal papers, along with their reference lists, are used to determine the minimal scientific knowledge necessary for generating the notions central to each focal paper. Attempts are made to trace how each type of knowledge was generated by various research communities. The results are discussed in terms of their potential implications in measuring, evaluating, understanding and managing the scientific research process.

Emerging research fronts in science and technology: patterns of new knowledge development.

Research fronts represent the most dynamic areas of science and technology and the areas that attract the most scientific interest. We construct a methodology to identify these fronts, and we use quantitative and qualitative methodology to analyze and describe them. Our methodology is able to identify these fronts as they form-with potential use by firms, venture capitalists, researchers, and governments looking to identify emerging high-impact technologies. We also examine how science and technology absorbs the knowledge developed in these fronts and find that fronts which maximize impact have very different characteristics than fronts which maximize growth, with consequences for the way science develops over time.

Tracking and predicting growth areas in science.

We explore the possibility of using co-citation clusters over three time periods to track the emergence and growth of research areas, and predict their near term change. Data sets are from three overlapping six-year periods: 1996-2001, 1997-2002 and 1998-2003. The methodologies of co-citation clustering, mapping, and string formation are reviewed, and a measure of cluster currency is defined as the average age of highly cited papers relative to the year span of the data set. An association is found between the currency variable in a prior period and the percentage change in cluster size and citation frequency in the following period. The conflating factor of "single-issue clusters" is discussed and dealt with using a new metric called in-group citation.