Hard science Totally Explained

Everything about Hard Sciences totally explained

Hard science is a term used to describe certain fields of the natural sciences or physical sciences that are perceived to be more accurate than other sciences like the social sciences. The hard sciences usually rely on experimental, empirical, quantifiable data or the scientific method and focus on accuracy and objectivity.
   The hard versus soft distinction is controversial in some circles. Although associated with notions of scientific realism, this distinction is drawn more from commonsense than a deep immersion in the philosophy of science. Much work by modern historians of science, starting with the work done by Thomas Kuhn, has focused on the ways in which the "hard sciences" have functioned in ways which were less "hard" than previously assumed, emphasizing that decisions over the veracity of a given theory owed much more to "subjective" influences than the "hard" label would emphasize (and begin to question whether there are any real distinctions between "hard" and "soft" science). Some, such as those who subscribe to the "strong program" of the sociology of scientific knowledge, would go even further, and remove the barrier between "hard science" and "nonscience" completely.
   Despite these objections, hard versus soft distinction is popular and widely used. One perceived difference supporting the distinction is the degree to which conclusions in different fields are controversial within those fields. Some believe that conclusions from physics or chemistry tend to be less controversial among physicists and chemists, versus how much of political science is controversial among political scientists. However, in most physical sciences there has been extensive debate about issues like whether atoms exist and whether randomness is inherent in subatomic particles. Russ Roberts from George Mason University claims that although many people romanticize about the objectivity of the so-called hard scientists, many physical scientists constantly engage in controversies and arguments.
   There is much difficulty distinguishing between soft and hard sciences because many social sciences, like economics and psychology, use the scientific process to formulate hypotheses and test them using empirical data. Furthermore, many social scientists engage in experimental work within the field of experimental economics. In most cases the methodology used by practitioners of the so-called soft scientist are the same as those used by practitioners of the hard sciences and the only difference is the object studied. Physical scientists tend to look at atoms, energy, waves, etc while social scientists tend to look at societies, individuals, firms, etc. The argument that societies, nations, and so on tend to display behavior that's more unpredictable than the behavior of atoms, waves, and so on, is also shaky because of advances in Quantum Physics that illustrate just how unpredictable subatomic particles are. Furthermore, the behavior of small units aggregated can yield behavior that's more predictable than the behavior of the small units themselves. This is due to aggregation canceling out randomness.
   In all experimental or empirical sciences there's a need to set up experiments. One necessary feature of experiments is the need to control all factors. It may be hard to control all factors in an experiment because the experimenter may not account for all factors. This problem exists in the social sciences and the physical sciences. To establish causation the experimenter needs to have a control group where only one variable, the variable of interest, is changed, and all other variables held constant. The difficulty is in how to control for all other variables when there could potentially be infinite variables.
   The graphism thesis maintains that hard sciences such as natural sciences make heavier use of graphs than soft sciences such as sociology. However, Bill Mann claims that an example of a discipline that uses graphs heavily but isn't at all scientific is technical analysis.

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