Issue Date: April 4, 2011
Rethinking Models And Polymers
The Feb. 14 letters section (page 2) contained two items, and I would like to comment on both.
Agustin Colussi made me aware that others share my belief that mathematical models have limitations to their predictive power. These arise not only from the specific function(s) chosen but also from the accuracy and range of the data used to detail the model. In addition, it must be remembered that, regardless of the deductive aspects of mathematics, science is primarily inductive. With these limitations, I find myself being skeptical about many of the results, mathematical or otherwise, being projected as conclusive.
Joseph Castellano pointed out the confusion regarding many kinds of polymers; that is, substances whose molecular structures show many repeating units, with “many” and “units” being somewhat open. Other terms such as plastic, elastomer, rubber, and even slime refer to the physical form. Thermoset, cross-linked, even glue provide additional information relative to use. To further confuse the issue, although covalent bonds usually predominate, ionic and hydrogen bonds can also contribute to a polymeric structure. By some definitions, metals might be considered polymers!
Colussi informs readers that he circulates a 1994 paper by Naomi Oreskes which points out that a model is not the thing being modeled, and agreement with observations is not a guarantee that the model will work given different conditions. Given just this observation, it’s a wonder that scientists make models at all.
One of the primary purposes of making models is to understand the system being modeled. It is important to recognize, however, that models may have predictive power for one property but not for others. Also, if adding improvements to the model gives no qualitative change, then the original model probably contained most of the important physics.
Colussi’s letter was no doubt prompted by Oreskes’ new book, “Merchants of Doubt” (C&EN, Jan. 17, page 38). Part of the doubt merchandising is the quoting of people (for example, weapons physicists) who are scientists stating opinions about areas outside their area of expertise (for example, climate modeling and cell biology). Colussi closes with the inference that it is acceptable to be skeptical of models and to have valid opinions but not loudly voice them.
I am intrigued by this concept of opinions in science and by skepticism of areas of science in which one is not an expert. If a person knows no science at all yet loudly voices opinions, he or she merely adds noise and confusion. Their skepticism does not derive from understanding, but from ignorance. There is a famous research paper by David Dunning and Justin Kruger, “Unskilled and Unaware of It: How Difficulties in Recognizing One’s Own Incompetence Lead to Inflated Self-Assessments” (J. Pers. Soc. Psychol. 1999, 77, 1121), which applies even to weapons physicists.
Science is based on facts and evidence, and keeping it this way is desirable. As educators, we need to teach students how to find reliable sources for science, how to recognize expertise in a speaker, and to disregard opinions no matter how much they agree with one’s political or religious beliefs.
Tracy P. Hamilton
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