Q20 - Criminals released from prison on parole

[SJK493]

Given the argument that intensive supervision is no more effective than routine supervision in preventing criminals from committing additional crimes, that they are not distinguishable, I was left with answer choices (C) and (E). I was wondering if (E) would work as a Justify the Conclusion Answer and why it is incorrect as a Necessary Assumption.

As for the correct answer (C), wouldn’t this be a mere restatement of the premise that ‘the percentage of released criminals arrested while under supervision is the same for intensive supervision as for routine supervision’?

How would I distinguish these answers?

[ohthatpatrick]

This is an oft-recurring LSAT argument template that's great to learn:
we could call it an ANTI-CAUSAL conclusion.

In tons of arguments, LSAT authors conclude that "one thing DID cause another thing",
but these anti-causal conclusions are more rare. They're trying to prove that "something DIDN'T make a difference".

Here's the anti-causal argument structure:

premise: Thing 1 has trait X, while Thing 2 does not
premise: yet Thing 1 and Thing 2 ended up the same.
conclusion: so, clearly, trait X has no causal effect

If you were going to argue that "trait X did have some effect", then how would you explain the tie?

You have to find some way to differentiate the two Things, so that they don't feel like they were STARTING from the same reference point.

These anti-causal arguments are saying, "Since they reached the finish line together, they were equally fast",
and we're objecting "Wait, one of them had a 20 yard head start! They didn't start from the same line. The one that had to play catch-up to get to the finish line at the same time was faster."

A simpler LSAT example: "Dave and Buster are equally good LSAT tutors, since they both get their students to score an average of 165 on the test."

What if Dave's students have an average incoming score of 159 and Buster's students have an average incoming score of 140?!
That would make Buster seem like a much better tutor.


In Q20, the author was saying "INTENSE supervision clearly made no difference, because group A and group B behaved similarly."
And we're objecting, "Whoa .. maybe group A is a much bigger group of troublemakers to begin with than group B is. If intense supervision got group A to behave like group B, then we're impressed with the effect of intense supervision!"


On Necessary Assumption, if you negate the correct answer, it turns into a big objection.
When we negate (C), it's says that "the proportion of arrests to crimes was way higher for the intensely supervised group".
WTF does that mean?

Let's mentally think through some numbers:
10 arrests to 50 crimes committed
vs.
10 arrests to 20 crimes committed

Which of those is the HIGHER proportion?

This gets pretty mathy. 10/50 < 10/20

1/5 < 1/2

So 10 arrests for every 20 crimes is a HIGHER proportion than 10 arrests for every 50 crimes.

10 for 20 is a pretty good rate of prevention! (50% of crimes prevented)
10 for 50 is not as good (20% of crimes prevented)

Negating (C) is saying, "The intensely supervised group had 50% of their crimes prevented whereas the routinely supervised group had 20% of its crimes prevented".

Does that weaken the argument?

Yes! The author concluded that "intense supervision is no more effective at preventing criminals from committing additional crimes".
The negation of (C) says "intense supervision IS more effective: it prevents 50% of crimes, while routine only prevents 20% of crimes".

It's not a restatement of the premise, because the premise said
"an equal percentage of intensely supervised CRIMINALS and routinely supervised CRIMINALS get arrested".

The subtle shift in the author's argument is from criminals to crimes.

Even though the same percentage of CRIMINALS get arrests (the premise)
that doesn't mean the same percentage of CRIMES get arrests (the negation of C)

So intense supervision might not be more effective in preventing criminals FROM BEING ARRESTED
but it could still be more effective in preventing criminals FROM COMMITTING ADDITIONAL CRIMES



(E) is an irrelevant concern because it's talking about the number of criminals. We wouldn't care whether the overall number of intensely supervised was bigger than the pool of routinely supervised, or vice versa. Since we're dealing with per capita statistics ("proportion / ratio / fraction / percent"), the numbers don't matter.

There might be more people who die each year of an alcohol overdose than of a heroin overdose.
But that higher total for alcohol is because way more people consume alcohol.
Per capita / proportional statistics are more informative.

If we learn that only 3% of alcohol consumers overdose while 25% of heroin users overdose, we will correctly judge that heroin carries a bigger risk of overdose than alcohol.

In other words, it made sense for the argument to be speaking in terms of percentage / proportion, and to judge statistical trends you don't really care what the raw numbers are (as long as the sample size is big enough to be fairly trustworthy).

Hope this helps.