A question about how one team would respond to a bolded claim tests how you connect two texts’ views. Read the question for who answers whom, then put the claim you’re asked about and its reason in a few words. Read the responding team’s view and ask whether it disagrees with the claim, adds limits to it, or applies it to a new case. Wrong choices can take the right view but fail to use the responding team’s own reason.
Hints
- Hint 1
The team in Text 2 is doing the responding. Read the bolded claim in Text 1, paying attention to how strongly it predicts what future estimates can show.
- Hint 2
Compare where and how often samples are taken in the two texts. How do those differences relate to Text 1’s reason for its claim?
- Hint 3
Judge the bolded claim from Text 2’s closing sentence. What does the team say its measurements can support?
Step-by-step
Compare the claim, method, and view
Step 1Pin down the claim and its reason
Text 1 bases its bolded prediction on the available data are too sparse and inconsistent. Which part of that prediction must Text 2’s team answer? The claim global totals for ocean microplastics will unavoidably remain approximate says the limit must remain, not only that ship-towed nets have weaknesses today.
- Step 2
Connect the new method to the old gaps
Does the new method leave those gaps unchanged? The floats sample from the surface to 1,000 meters and repeat vertical profiles weekly, which adds depth and time coverage beyond brief surface trips. Their measurements are calibrated against laboratory standards and assimilated into circulation models, meaning they’re checked and used in models of ocean flow. Text 2 offers a way to fill the gaps behind Text 1’s claim.
- Step 3
Name the view and test the reasons
What view follows from the team’s closing claim? It says the combined measurements yield robust global estimates, which rejects Text 1’s claim of an unavoidable limit. The response keeping totals approximate rather than reliable holds onto the limit the team challenges. The response calling for much longer deployments also misses the team’s reason: Text 2 reports weekly sampling and says this approach already supports global estimates.
- Step 4
Match the reason and the strength
The response about depth-resolved, repeatedly collected measurements gives the team’s own reason for challenging Text 1. Does reduce uncertainty enough promise more than yield robust global estimates? No: a dependable estimate needn’t be a perfectly exact count, so the response keeps the team’s claim without saying all uncertainty disappears. Choice C.