I think the generalised lesson to be learned is that in reducing complexity (and all modelling requires reducing complexity), you get to make decisions about which bits of data are cut out, and this is a decision that can introduce bias. We can't just blindly trust reductions, especially in areas where there are competing interests. This is why transparency is so important! If I can reproduce your methodology, I can critique it for bias.