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    It is not the case that Matching and protocol-based allocation presuppose a complete causal model, making them epistemically circular when the causal structure is precisely what is under investigation.

    ?Set your confidence on the premises below to see your aggregate.

    Reasons For

    1 perspective
    Reason for
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    • 1.Matching uses only covariate balance to reduce bias, not causal model specification—balance is a distributional property independent of causal claims.
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    • 2.All empirical inquiry requires some background assumptions; epistemic circularity is not unique to matching and doesn't disqualify useful methods.
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    • 3.Protocol-based allocation can be validated through sensitivity analysis and robustness checks without fully specifying the causal model upfront.
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    Reasons Against

    1 perspective
    Reason against
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    • 1.Matching methods require specifying which variables confound treatment-outcome relationships, presupposing causal knowledge they claim to discover.
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    • 2.Using pre-treatment covariates assumes causal direction (confounders precede outcomes), but this temporal ordering is itself a causal assumption needing justification.
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    • 3.Protocol-based allocation decides which variables to control before seeing data, smuggling in untested causal assumptions into the study design itself.
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