Networks of predictions [An article from: Futures]

This digital document is a journal article from Futures, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Certain predictions stand out from others, irrespective of their accuracy, because they integrate many other predictions into a rich web of expectation. They can be identified by constructing, for any given issue, a network that maps the causal or contingent relationships that are often explicitly posited within a list of topically related predictions. The network has a distinctive structure. Many nodes (representing predictions) have a few links (indicating causal influence) but a few nodes have many. This distributional bias is a defining characteristic of non-random, scale free networks and influences the pattern of growth. New predictions tend to link with the already well connected, producing networks that are organized around a few, centrally located nodes. These identify the predictions perceived, within a community of informed opinion, to be the most ''causally active''. A network is a cognitive map that aggregates our current understanding of an issue, reconfigures to incorporate new information as an issue evolves over time, and offers a metric for weighing the relative contribution of any one prediction in structuring our collective thinking about the future. Illustrative material is drawn from a relational database of some 350 predictions about global water scarcity.