Demand code and/or data as a condition of peer review? It is still relatively uncommon for social scientists to share data or code as a part of the peer review process. I feel that this practice runs contrary to notions of replicability and reproducibility and have a desire to voice opposition to instances in which manuscripts are submitted without data and code. 

Where, however, is such opposition appropriately expressed? 

I am specifically curious about whether or not it is appropriate to refuse to review an article in the absence of code or data. 

UPDATE

I'm going to watch this for a couple of days to see what surfaces. FYI I cross-posted this to Andrew Gelman (http://andrewgelman.com/2015/09/14/its-not-so-easy-to-share-data-and-code-and-there-are-lots-of-bureaucrats-who-spend-their-time-making-it-even-more-difficult/) for those who are interested in seeing his response and the response of his followers...
I would suggest first spending a little bit of time reflecting to yourself on why you want to see sharing of code and data, and which code and data you would want to be shared.  Is it more ideological in nature ("information wants to be free"), or at its root is it a belief more about scientific ethics and efficacy?

I am almost certain that you do not actually want all data and code to be shared.  For example, you probably do not want identifying information about subjects to be shared.  Likewise, you probably do not care too much about little bits of utility code that don't have anything much to do with the science.  Where do you draw your boundaries and why?

The reason I would suggest doing that, is that you will then be in a good position, as a reviewer, to persuasively argue for the inclusion of code and/or data for objective reasons that the editor and author are more likely to agree with, even if their personal preferences are different.  I don't think you'll have much effect by refusing to review (unless you can get a lot of colleagues to exert pressure along with you), but I think you may make much more difference by refusing to accept poorly justified conclusions in the absence of result and method information to support them.