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fletcher

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Defamiliarization audit for empirical output. Systematically interrogates every feature of a figure, table, or set of results — not just the main finding. Named for Jason Fletcher, who asked about the spike at t=1 when everyone else was looking at t=2. Use when you have output and are about to interpret or report it.

When to use

• Auditing figures before description
• Interpreting tables before writing
• Reviewing results before write-up
• Identifying unexplained features in output
• Checking for misinterpretation of data
• Defamiliarizing empirical output

When not to use

• Auditing implementation correctness
• Checking for coding errors
• Verifying replication failures
• Auditing after writing is done
• Replacing Referee 2

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