An environmental economist observed that cities implementing a 'green canopy' initiative—planting shade trees along commercial corridors—experienced a 15% higher increase in local retail revenue over five years compared to cities without the initiative. The economist concluded that the presence of the green canopy directly stimulated local consumer spending.
Match each potential explanatory objection (left) with the specific 'defender assumption' (right) that the economist's argument must make to effectively neutralize that objection.
- Retail areas already experiencing significant economic booms were much more likely to have the surplus tax revenue required to invest in aesthetic improvements like green canopies.An anticipated or ongoing increase in commercial prosperity was not the primary prerequisite for municipalities to initiate the arboricultural projects.
- The state offered commercial revitalization grants that mandated tree planting, but these grants also heavily funded massive advertising campaigns for the local businesses.Parallel promotional subsidies provided alongside the environmental grants did not single-handedly generate the observed economic uplift.
- The pilot program for the green canopy initiative exclusively selected cities that had recently completed multi-million-dollar modernizations of their shopping districts.The initial criteria for participating in the arbor program did not restrict entry solely to locales with newly upgraded commercial infrastructure.
- The retail revenue data for cities without the green canopy included vast industrial zones with no retail presence, artificially suppressing their average revenue figures.The comparative economic metrics used to evaluate the non-participating municipalities did not disproportionately incorporate data from non-commercial sectors.
Cevap
The reverse causality objection matches with the assumption that commercial prosperity was not a prerequisite. The third-variable confound (advertising) matches with the assumption that promotional subsidies weren't the sole cause. The selection bias objection matches the assumption that entry wasn't restricted to upgraded locales. The data measurement flaw matches the assumption that non-commercial sectors didn't skew the comparative metrics.
Each correct pair accurately maps a specific vulnerability in causal reasoning to the precise negative statement (defender assumption) required to close that vulnerability. An argument concluding X causes Y must assume Y did not cause X, an outside factor Z did not cause Y, the sample exhibiting X was not inherently biased to show Y, and the baseline data for the absence of X was not artificially skewed.
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Anahtar Kavram
Ruling Out Alternate Explanations (Defender Assumptions)