I certainly agree that people shouldn't be using techniques they don't understand. But to address the main point - there are two separate things to consider wh

I certainly agree that people shouldn't be using techniques they don't understand. But to address the main point - there are two separate things to consider when assessing a paper's methods. First is the methodology, which as you say is always included in the paper. But secondly, and equally importantly, is the implementation. Agreeing with the methodology does not make me confident in the results. Someone wrote (probably) a lot of code to generate the analysis, and the likelihood that it contains bugs is high. They may or may not affect the outcome. Without seeing the code, I'm not going to trust the results. Of course, I don't expect to read the source code of every analysis, but if it's open to scrutiny by the community, and the results are of any importance, it will be validated. The problem is actually worse in many experimental methods, where the results rely completely on the practitioner having done exactly what they say they did and done it correctly. No source code to publish there, but that doesn't excuse not publishing analytical code when it is available.