Progress and Its Problems: Towards a Theory of Scientific Growth by Larry Laudan

Progress and Its Problems: Towards a Theory of Scientific Growth Larry Laudan ebook
ISBN: 0520037219, 9780520037212
Publisher: University of California Press
Format: pdf
Page: 268

I do think Laudan at least makes a good case that the rationality of scientists accepting a theory can be understood in terms of how effective the theory is at solving the problems the scientists are concerned with. In other words, you've run up against the limits of our current knowledge; to make any further progress is going to take an innovation that's not yet a part of our scientific lexicon. What a theory is supposed to do etc etc. Although coarse-grain system dynamics models were used in the past to predict the growth and development of scientific research, among the limitations of their use include (1) lack of heterogeneity in terms of individuals' decisions, actions, career choices, as well as learning and . An explicit model of knowledge production that converts human, financial, and knowledge capital into resources (e.g., open problems, skills), which are then transformed into solutions and products. The great unsolved problems of your time look like missing puzzle pieces, while the tools, equations and current theories begin to look like misshapen pieces that don't quite fit where they're supposed to. Progress and Its Problems: Toward a Theory of Scientific Growth. I think there have been some successes, but a lot of Science is a combination of gathering facts and making theories; neither can progress on its own. Larry Laudan's 'Progress and its problems: Towards a theory of scientific growth' explains this beautifully. I think Chomsky is wrong to push the needle so far towards theory over facts; in the history of science, the laborious accumulation of facts is the dominant mode, not a novelty. It's true there's been a lot of work on trying to apply statistical models to various linguistic problems. Most importantly, Laudan implicitly assumes that we can't specify a standard for measuring scientific progress (say, truth) if we have no epistemic access to evidence that would allow evaluation of how far science has progressed towards that standard. Image credit: Lawrence Berkeley Laboratory / Paul Preuss / Michael Crommie.