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Meteorologists say that if only they could design an accurate mathematical model of the atmosphere with all its complexities, they could forecast the weather with real precision. But this is an idle boast, immune to any evaluation, for any inadequate weather forecast would obviously be blamed on imperfections in the model.
Which of the following, if true, could best be used as a basis for arguing against the author's position that the meteorologists' claim cannot be evaluated?
| Text from Passage | Analysis |
| Meteorologists say that if only they could design an accurate mathematical model of the atmosphere with all its complexities, they could forecast the weather with real precision. |
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| But this is an idle boast, immune to any evaluation, for any inadequate weather forecast would obviously be blamed on imperfections in the model. |
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The argument starts by presenting the meteorologists' claim about perfect weather forecasting, then immediately attacks this claim by arguing it can't be properly tested or evaluated.
The meteorologists' claim about accurate weather forecasting cannot be evaluated because any failures would be blamed on model imperfections rather than the theory itself.
The author uses a single premise to support the conclusion: since bad forecasts would always be blamed on the model being incomplete rather than the theory being wrong, there's no way to actually test whether the meteorologists' claim is valid. This creates what the author sees as an unfalsifiable statement.
Weaken - We need to find information that reduces belief in the author's conclusion that the meteorologists' claim cannot be evaluated
The author makes an absolute claim about evaluation impossibility - that ANY inadequate forecast would OBVIOUSLY be blamed on model imperfections, making the theory immune to ANY evaluation
To weaken the author's position, we need to show that the meteorologists' claim CAN actually be evaluated in some meaningful way. We should look for scenarios where:
This choice discusses unusual data configurations allowing precise forecasts without understanding exact mechanisms. However, this doesn't address the author's core concern about evaluation impossibility. The author isn't questioning whether accurate forecasts are possible, but whether the meteorologists' specific claim about mathematical models can be evaluated. This choice sidesteps the evaluation issue entirely.
This directly weakens the author's position by establishing a measurable relationship between model improvements and forecast precision. If we can observe that better models consistently produce better forecasts, then we DO have a way to evaluate the meteorologists' claim. This contradicts the author's assertion that the claim is 'immune to any evaluation' because it shows we can test whether the theory holds up in practice.
The fact that models for volcanic eruptions are being constructed doesn't address whether the meteorologists' claims about general weather forecasting can be evaluated. This is about a specific type of modeling that doesn't resolve the broader evaluation problem the author identifies.
Current forecast accuracy statistics don't help us evaluate the meteorologists' future claims about what they could achieve with perfect models. The author isn't questioning current forecasting ability, but rather arguing that we can't properly test the meteorologists' theoretical claim about perfect models.
If meteorologists admit they can't currently build the accurate model they're discussing, this actually supports the author's position rather than weakening it. It reinforces that the claim might indeed be impossible to evaluate since the proposed solution doesn't currently exist.