A recent study of municipal programs found that cities instituting "pay-as-you-throw" waste disposal systems—where residents are charged a fee based on the weight of their non-recyclable trash—saw a 40 percent increase in the total tonnage of materials collected in residential recycling bins during the first year. The study's authors conclude from this that the financial penalty successfully motivated residents to properly sort and recycle a much larger proportion of their eligible household waste.
Which one of the following, if true, most seriously weakens the argument?
- AMany neighboring municipalities that use traditional flat-fee waste disposal systems have recently been forced to reduce the frequency of their recycling collection.
- BResidents in the studied cities received monthly utility statements that prominently displayed the exact financial savings they achieved by utilizing the recycling bins.
- In the year following the system's implementation, recycling facilities in these cities reported a drastic increase in heavy, non-recyclable garbage being improperly disposed of in residential recycling bins.Cevap
- DThe scales used by the municipal trucks to weigh the recycling bins were found to be defective, consistently overestimating the weight of the collected materials.
- EA 40 percent increase in recycling tonnage in the studied cities constitutes a smaller absolute weight than a 15 percent increase would in most major metropolitan areas.
Cevap
The correct answer is the one stating that facilities reported a drastic increase in heavy, non-recyclable garbage being improperly disposed of in residential recycling bins.
The correct answer successfully weakens the argument by providing an alternative explanation for the 40 percent increase in tonnage. If residents are putting heavy, non-recyclable trash into their recycling bins to avoid paying the new weight-based fees for normal trash, then the increased weight in the recycling bins does not mean they are 'properly sorting and recycling' more eligible waste. This completely severs the logical link between the statistical premise and the behavioral conclusion.
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Identifying Alternative Explanations for Correlated Data
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