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It is not the case that Cases with structurally different causal histories belong to different explanatory types, regardless of phenomenological similarity at the level of sense-data.
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Reasons For
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1.
Explanatory type classification should track what matters for prediction and intervention. If causal differences produce identical observable outcomes, they may not constitute different explanatory types.
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2.
Occam's razor favors unified explanations. Multiplying explanatory types based on unobservable causal differences violates parsimony without empirical justification.
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3.
Phenomenological similarity at the level of sense-data is precisely what determines explanatory adequacy for most practical purposes and scientific applications.
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Reasons Against
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Reason against
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1.
Explanation aims to reveal underlying mechanisms, not merely describe appearances. Identical appearances from different causes represent genuinely different explanations.
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2.
Scientific understanding requires causal-mechanistic knowledge. Two systems with identical phenomenology but different causal structures require distinct scientific explanations.
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3.
Counterfactual dependence varies with causal structure. Systems with different causal histories show different modal properties, so they belong to different explanatory types.
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