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The book I'm reading Critical Thinking by Brooke Noel Moore, Richard Parker says that the following is an argument.

John Montgomery has been the Eastern Baseball League’s best closer this
season. Unfortunately, when a closer fails, as Montgomery did last night,
there’s usually not much chance to recover. Draw your own conclusion.

But the "Draw your own conclusion." part doesn't convince me. It seems that instead of a command to draw a conclusion, an argument should require an explicit statement, right?

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  • What is the question? Commented May 21, 2023 at 1:42
  • This is a classic example of a well-known linguistic trope and that's why ... draw your own conclusion(s). 😁
    – Hudjefa
    Commented May 21, 2023 at 1:54
  • The implied, unstated conclusion would be, "There's wasn't much chance to recover after Montgomery failed last night." It's basically modus ponens. "When a closer fails, there's not much chance to recover. A closer failed. Therefore, there wasn't much chance to recover."
    – causative
    Commented May 21, 2023 at 5:04
  • Edited to stave off closure by highlighting the question at hand.
    – J D
    Commented May 22, 2023 at 16:11

1 Answer 1

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It's nice when arguments are put forth as syllogisms: premise 1, premise 2, and therefore conclusion. However, such simple arguments tend to exist in textbooks. In real life, conclusions are seldom so certain, and in sporting events, ever more so. In the example:

John Montgomery has been the Eastern Baseball League’s best closer this season. Unfortunately, when a closer fails, as Montgomery did last night, there’s usually not much chance to recover. Draw your own conclusion.

We can strip out some of the extraneous language:

P1: Montgomery is a closer and failed.
P2: If a closer fails, then there’s usually not much chance to recover.
C: (If things go as usual, there's not much chance Montgomery will recover.)

What makes this argument different is that instead of an implicit, unstated premise, there's an implicit unstated conclusion with instructions to come to the conclusion. So, yes, there's an argument, though from a rhetorical standpoint, one often trumpets the conclusion rather than hide it away for the listener to put together. Is it modus ponens? Looks like its close, but not exactly:

P1: Fail(Closer(Montgomery))
P2: IF Fail(closer(X)) AND usual(events) THEN small(P(recover(X)))
C: IF usual(events) THEN small(P(recover(Montgomery)))

which symbolically is:

P1: P
P2: P AND R THEN Q
C: R THEN Q

Looks like the adverb 'usually', which is a linguistic hedge adds some added complexity by introducing a condition to arrive at the truth of the second premise which complicates the argument. That is, in modus ponens, one arrives at the conclusion with certainty, but the conclusion of this argument is itself a conditional.

So, this language, which is much closer to what one would see outside of textbook on syllogisms, is indeed an argument, one which admits a defeator (SEP) explicitly. That is, to avoid the conclusion, one simply must make an argument that events surrounding the performance of the closer are not usual. Perhaps, Montgomery's outcome, for instance, was uncharacteristic of the prior base of events, failed because the ref was in on fixing the game, and after getting caught, was removed from his position. In that case, one might argue that despite the prior failure, Montgomery will recover.

So, unlike an Aristotelian syllogism, which is a very simple form of argumentation that arrives at a simple conclusion, we have a more sophisticated argument because it:

  1. Does not explicitly state the conclusion.
  2. Has extra information that one usually omits from a textbook problem.
  3. Contains a linguistic hedge.
  4. Has a conclusion that is itself conditional upon the criterion 'usual'.

Think about it. In sporting events, where things are never certain, an intelligent analyst won't make strong, certain claims, but rather hedge their bets with if's. So, not only is this an argument, but it's an intelligent one because of the way it deals with uncertainty using natural language.

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