This paper is what I have been yelling about for a few years now: the true danger in empirical social sciences is more often "researchers degrees of freedom" in design, data curation, measurement, choice of method. The big threat is not outright fraud or p-hacking (although these are problems) or even biases against publishing null results. Its those hundreds of small choices researchers make when preparing their papers -- none of which are sins of omission or commission. They're good faith human decisions with no malice. Yet, two equally good faith moves can generate different results. This apparently forthcoming paper in Journal of Economic Literature asked 146 research teams to estimate the same causal effect using the same underlying data. In unconstrained setups, they arrived at massively different results. Even in more constrained setups (with more directives), they showed differences. All of which came from picking the design and curating the data (cleaning). Huge! I would reformulate the problem as unexamined researcher degrees of freedom, rather than methodological freedom itself! Indeed, what we need is a strong contestability (and good faith) to point out what could be happening.