Question

During the nineteenth century, Britain's urban population increased as its rural population diminished. A historian theorizes that, rather than industrialization's being the cause, this change resulted from a series of migrations to urban areas, each occasioned by a depression in the agrarian economy. To test this hypothesis, the historian will compare economic data with population census data.
The historian's hypothesis would be most strongly supported if which of the following were found to be true?

• A. The periods of greatest growth in the industrial economy were associated with a relatively rapid decline in the rural population.
• B. The periods of greatest weakness in the agrarian economy were associated with relatively slow growth in the population as a whole.
• C. Periods when the agrarian economy was comparatively strong and the industrial economy comparatively weak were associated with a particularly rapid decline in the rural population.
• D. Periods when the agrarian and industrial economies were both strong were associated with particularly rapid growth in the urban population.
• E. The periods of greatest strength in the agrarian economy were associated with relatively slow growth in the urban population.

Hint:

Supporting a hypothesis isn't just about showing the correlation works in one direction. Showing that the correlation also works in reverse (the absence of the cause is linked to the absence of the effect) is a very powerful way to strengthen a causal claim and is a common pattern in critical reasoning questions.

Answer 1

Answer: (E)

Step 1: Understanding the Concept:
This question asks what finding would best support a historian's specific hypothesis. We need to clearly understand the causal relationship the historian is proposing.
Step 2: Key Formula or Approach:
The hypothesis is: Depression in the agrarian economy (Cause) \(\rightarrow\) Migration to cities / Urban growth (Effect).
To support a causal claim "If X, then Y," one can show two things:
1. When the cause (X) is present, the effect (Y) is also present.
2. When the cause (X) is absent, the effect (Y) is also absent. This is often very strong support.
Step 3: Detailed Explanation:
Let's analyze the options based on the hypothesis (Agrarian Depression \(\rightarrow\) Urban Growth):
- (A) This supports the traditional theory that industrialization (an urban "pull" factor) was the cause, which the historian is arguing against. This would weaken the hypothesis.
- (B) This discusses the overall population, not the rural-to-urban shift, so it's not directly relevant.
- (C) This states that agrarian strength led to rural decline (urban growth). This is the exact opposite of the hypothesis.
- (D) This doesn't isolate the key variable (agrarian depression), so it doesn't effectively test the hypothesis.
- (E) This option tests the "absent cause, absent effect" condition. "Greatest strength in the agrarian economy" means the cause (agrarian depression) is absent. "Relatively slow growth in the urban population" means the effect (rapid urban growth) is also absent. Finding that urban growth stalled when the farms were doing well strongly supports the idea that it was trouble on the farms that was driving people to the cities.
Step 4: Final Answer:
The finding that the urban population grew slowly when the agrarian economy was strong provides powerful support for the hypothesis by showing that the effect disappeared when the proposed cause was removed.