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Course Hero. "An Essay on the Principle of Population Study Guide." April 27, 2018. Accessed December 13, 2018. https://www.coursehero.com/lit/An-Essay-on-the-Principle-of-Population/.
Course Hero, "An Essay on the Principle of Population Study Guide," April 27, 2018, accessed December 13, 2018, https://www.coursehero.com/lit/An-Essay-on-the-Principle-of-Population/.
In "civilized nations," Malthus says, farmland exists in a state of "mixed pasture and tillage." In other words, some of it is devoted to grazing cattle, while the rest is used for growing crops. The populations of such nations at present are "much greater than ever ... in former times." The increase is due to the fact that these countries now produce much more food than they did in, say, the time of Julius Caesar (first century BCE).
With this in mind, Malthus critiques David Hume's writings on "the populousness of ancient and modern nations." Hume, he says, is confusing the rate of population growth with the overall size of a population. The factors that make a population increase quickly at any given time do not necessarily mean the population is already large at that time. To the contrary, when there are strong "encouragements" to population growth, it is likely because the population is small and resources are plentiful. Likewise, the factors that discourage population growth tend to arise when a population is large and resources are scarce.
At present, Malthus observes, population growth in Europe is slow. In some nations, the birth rate barely matches—or even falls short of—the death rate. The reason, he says, comes down to two kinds of "checks" (hindrances) to population. Reluctance to start a family is a preventive check to population growth, while disease and malnourishment are positive checks. Malthus gives English society as an example of how preventive checks operate. Among the poor, the working class, and even the gentry, he says, men are reluctant to marry for various reasons. The well-to-do are aware that supporting a wife and children will cost money, leaving them less able to maintain their social standing. Laborers and servants fear that although they can support themselves well enough, they will not be able to provide for a family.
Scottish philosopher David Hume (1711–76) was one of the foremost political and ethical thinkers of 18th-century Britain. His works covered a wide swath of topics, including morality, history, and the philosophy of mind. Here, Malthus critiques Hume's essay, "Of the Populousness of Ancient Nations," from his 1742 book Essays, Moral, Political, and Literary. In this work, Hume considers the writings of ancient historians as a source of information on the populations of classical Greece and Rome. He attempts to combine the historians' population estimates with qualitative information about how wealthy or poor societies were at various periods in history.
Although Malthus criticizes Hume's conclusions, it should be noted he uses a very similar style of inferential reasoning to Hume's in "Populousness." Both men use available facts and figures as just one form of support for their argument. They happily fill in the gaps with less quantitative, less rigorous material such as quotations from respected authors, hearsay, and commonsense observations. The result, in each case, is something partway between philosophy and science, between an informal "what-if" narrative and a scientific interpretation of data. The numbers, of which Malthus provides plenty in Chapter 7, don't "tell the story" by themselves.
At the time Malthus wrote the Essay, it should be remembered the study of statistics was in its infancy. Tools for evaluating the quality and usefulness of data were still largely undeveloped. A few pioneers, such as Thomas Bayes (1702–61) and Pierre-Simon, marquis de Laplace (1749–1827), had begun—or would soon begin—working out the science of probability. Statistics as people know it today, however, is the product of many 19th- and 20th-century inventions. Thus, it is not too surprising to find that Malthus's reasoning about statistical data is often casual and ad hoc.