Diferenças

Aqui você vê as diferenças entre duas revisões dessa página.

--- geopro:pedro:complexity [2008/03/19 14:24] – 150.163.67.167
+++ geopro:pedro:complexity [2009/01/30 16:17] (atual) – pedro
@@ Linha 1: / Linha 1: @@
+====== Complexity ======
+{{http://www.leg.ufpr.br/~pedro/figures/scale.jpg  }}
+=====Terms=====
+  * **Lowrys’s Principle (1965):** the only true test of a model is when it is fitted for one situation and then is tested in a different situation.
+  * **[[http://en.wikipedia.org/wiki/Occam's_Razor|Occam's razor (14th-century)]]:** All other things being equal, the simplest solution is the best. //lex parsimoniae//.
+=====Papers=====
 ====More is Different====
 |P. W. Anderson, 1972| Science| [[http://leg.ufpr.br/~pedro/papers/science/moreisdifferent.pdf|pdf]]|
@@ Linha 52: / Linha 63: @@
   * the evolutionary model, in which incremental changes can become radically variations.
 The paper shows a couple of examples of each case.
+====Seductive Simulations?====
+|Myanna Lahsen, 2005| Social Studies of Science 35(6):895–922| [[http://www.leg.ufpr.br/~pedro/papers/seductive-simulations.pdf|pdf]]|
+\\
+**Abstract:** This paper discusses the distribution of certainty around General
+Circulation Models (GCMs) – computer models used to project possible global climatic
+changes due to human emissions of greenhouse gases. It examines the trope of
+distance underpinning Donald MacKenzie’s concept of ‘certainty trough’, and calls for
+a more multi-dimensional and dynamic conceptualization of how uncertainty is
+distributed around technology. The certainty trough describes the level of certainty
+attached to particular technoscientific constructions as distance increases from the site
+of knowledge production, and proposes that producers of a given technology and its
+products are the best judges of their accuracy. Processes and dynamics associated with
+GCM modeling challenge the simplicity of the certainty trough diagram, mainly
+because of difficulties with distinguishing between knowledge producers and users,
+and because GCMs involve multiple sites of production. This case study also challenges
+the assumption that knowledge producers always are the best judges of the accuracy
+of their models. Drawing on participant observation and interviews with climate
+modelers and the atmospheric scientists with whom they interact, the study discusses
+how modelers, and to some extent knowledge producers in general, are sometimes
+less able than some users to identify shortcomings of their models.
+\\