Objectivity (science)

value that informs how science is practiced and how scientific truths are discovered

Objectivity in science means that scientific ideas and measurements are tested. That means they are independent from the individual scientist (the subject) who proposes them. In other words, if scientist A claims something, scientist B must be able to check whether A is right.

The evidence can (in principle) be shown to anyone who doubts it. The "in principle" bit is because some science needs complex machinery, and if you don't understand the machinery, you won't understand the results. But elementary science can often be shown in a classroom, or on television.

Some science does need a proper scientific education. To some extent the general public has to trust a qualified scientist to present the idea in some suitable form. That means on television or on the web, or perhaps in published articles or books. Most awards of the Nobel Prize in science are followed by presentations on various web channels.

It is generally agreed that, at least in some subjects, modern science needs a person to have some education before they can understand it. Specialist communicators often do this on television or the web. 150 years ago, people read science directly from books written by scientists like Faraday and Darwin. Now most people get their science from people who act as communicators of science.

Objectivity in measurementEdit

To avoid the variety in subjective (equivocal) interpretation of quantifying terms such as "green", "hot", "large", "considerable", and "negligible", scientists strive, where possible, to eliminate human senses by use of standartized measuring tools (meter stick, stopwatch, thermometer, etc.) and mechanical/electronic measuring instruments (spectrometer, voltmeter, timer, oscilloscope, gravimeter, etc.) for performing the actual measuring process, eliminating much of the perceptive variability of individual observers. The results of measurements are expressed on a numerical scale of standard units - so that everybody else understands them the same way. Where data must need be used, the ideal is to use "hard", "objective" criteria for assigning the classifications (see definition), such that different classifiers would get the same results.

LiteratureEdit

  • Dawkins, Richard 2003. A Devil’s Chaplain: selected essays. Phoenix.
  • Kuhn, Thomas 1962. The Structure of Scientific Revolutions. University of Chicago Press, 3rd ed. 1996.
  • Porter, Theodore M. 1995. Trust in Numbers: the pursuit of objectivity in science and public life. Princeton University Press.
  • Restivo, Sal 1994. Science, Society, and Values: toward a sociology of objectivity. Lehigh University Press.
  • Sokal, Alan & Bricmont, Jean 1997. Intellectual Impostures: postmodern philosophers’ abuse of science. Profile Books 2003.