Question Type:
Weaken (phrased like Flaw, but everything's prefaced by "fails to consider")
Stimulus Breakdown:
Conclusion: Standard recs for avoiding infection from meat-pathogens must be counterproductive.
Evidence: Ppl who follow standard recs are more likely to actually get infections from meat-pathogens than those who don't.
Answer Anticipation:
This is a classic Correlation -> Causality flaw. The author infers, from the correlation between "ppl who follow recs" and "ppl who contract diseases" that following the recommendations is CAUSING them to be more likely to contract the diseases. When an author sees that X and Y are correlated and assumes/concludes that X causes Y, we always consider two common alternative interpretations:
1. Maybe Y caused X (maybe having a history of contracting these diseases has led these people to now become people who follow the recs)
2. Maybe there's some third factor Z accounting for the correlation (maybe people on chemotherapy are therefore more likely to contract diseases and their doctors heavily emphasize following the standard recs).
Correct Answer:
E
Answer Choice Analysis:
(A) We're only talking about meat-based pathogens, so it's irrelevant whether these pathogens exist elsewhere.
(B) Cool. But many people DO precisely follow all the recs, and they're more likely to contract diseases, and we and this author are trying to figure out why that is.
(C) "Not all" = weak language alert. Who cares if "at least one microorganism disease does not have readily recognizable symptoms"?
(D) Are the "standard" recommendations "the appropriate set" of recommendations? We don't know. The correlation and the author suggest maybe not. There's no way to apply this answer since we don't know what is an "appropriate set" of recs.
(E) YES! Here's the ol' Reverse Causality answer. Y came first. They were already susceptible to meat-based infections, and THAT causes them to follow all the standard recs precisely.
Takeaway/Pattern: Any time the author's conclusion is Causal, we think
1. Is there some OTHER WAY to explain the background fact
(the 2 most common ways are Reverse Causality, Y caused X, and Third Factor, Z accounts for the correlation between X and Y)
or
2. What circumstantial facts would support/undermine the AUTHOR'S WAY
(most common way is Covariation -- more examples of cause/effect going hand in hand or not)
#officialexplanation