Online Appendix to "Yes, But What's the Mechanism? (Don't Expect an Easy Answer)''

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Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data (2017, background): “In offering recommendations for experimental research programs, Bullock, Green, and Ha (2010) highlighted that uncovering a mediating mechanism might be much harder than most social scientists realize.”
On the Overuse and Misuse of Mediation Analysis: It May Be a Matter of Timing (2015, background): “…features was undercut, however, when those authors acknowledged earlier that ‘‘researchers may reasonably try to manipulate mediators experimentally, though experimental mediation analysis can be problematic too (Bullock et al., 2010 [Bullock, Green, & Ha, 2010])’’ (Fiedler et al., 2011, p. 1236).”
Meaningful Mediation Analysis: Plausible Causal Inference and Informative Communication (2017, background): “…strong case for a specific causal direction between mediator and outcome, or between mediators, cannot be made it is good advice to refrain from statistical mediation analysis and treat the presumed mediators and outcome as separate, correlated outcomes of the treatment (Bullock and Ha 2011, 517).”
Advances in mediation analysis: a survey and synthesis of new developments. (2015, background): “Even when manipulation of M is possible, X may moderate the M → Y effect, or observed effects may characterize only a subset of the population (Bullock et al. 2010, Spencer et al. 2005).”