Liam Kofi Bright

Pre-publication peer review should be abolished. We consider the effects that such a change will have on the social structure of science, paying particular attention to the changed incentive structure and the likely effects on the behavior of individual scientists. We evaluate these changes from the perspective of epistemic consequentialism. We find that where the effects of abolishing pre-publication peer review can be evaluated with a reasonable level of confidence based on presently available evidence, they are either positive or neutral. We conclude that on present evidence abolishing peer review weakly dominates the status quo.

NOTE FOR CITATION PURPOSES: The DOI for this paper is 10.1086/684173

Social scientists report difficulties in drawing out testable predictions from the literature on intersectionality theory. We alleviate that difficulty by showing that some characteristic claims of the intersectionality literature can be interpreted causally. The formalism of graphical causal modeling allows claims about the causal effects of occupying intersecting identity categories to be clearly represented and submitted to empirical test. After outlining this causal interpretation of intersectional theory, we address some concerns that have been expressed in the literature claiming that membership in demographic categories can have causal effects.

Social scientists use many different methods, and there are often substantial disagreements about which method is appropriate for a given research question. In response to this uncertainty about the relative merits of different methods, W. E. B. Du Bois advocated for and applied `methodological triangulation'. This is to use multiple methods simultaneously in the belief that, where one is uncertain about the reliability of any given method, if multiple methods yield the same answer that answer is confirmed more strongly than it could have been by any single method. Against this, methodological purists believe that one should choose a single appropriate method and stick with it. Using tools from voting theory, we show Du Boisian methodological triangulation to be more likely to yield the correct answer than purism, assuming the scientist is subject to some degree of diffidence about the relative merits of the various methods. This holds even when in fact only one of the methods is appropriate for the given research question.

This paper addresses the problem of judgment aggregation in science. How should scientists decide which propositions to assert in a collaborative document? We distinguish the question of what to write in a collaborative document from the question of collective belief. We argue that recent objections to the application of the formal literature on judgment aggregation to the problem of judgment aggregation in science apply to the latter, not the former question. The formal literature has introduced various desiderata for an aggregation procedure. Proposition-wise majority voting emerges as a procedure that satisfies all desiderata which represent norms of science. An interesting consequence is that not all collaborating scientists need to endorse every proposition asserted in a collaborative document.

Social scientists use many different methods, and there are often substantial disagreements about which method is appropriate for a given research question. A proponent of methodological triangulation believes that if multiple methods yield the same answer that answer is confirmed more strongly than it could have been by any single method. Methodological purists, on the other hand, believe that one should choose a single appropriate method and stick with it. Using formal tools from voting theory, we show that triangulation is more likely to lead to the correct answer than purism, assuming the scientist is subject to some degree of diffidence about the relative merits of the various methods. This is true even when in fact only one of the methods is appropriate for the given research question.

Intersectionality theory explores the special sorts of disadvantage that arise as the result of occupying multiple disadvantaged demographic categories. One significant methodological problem for the quantitative study of intersectionality is the difficulty of acquiring data sets large enough to produce significant results when one is looking for intersectional effects. For this reason , we argue, simulation methods may be particularly useful to this branch of theorizing because they can generate precise predictions and causal dependencies in a relatively cheap way, and can thus guide future empirical work. We illustrate this point through models which show that intersectional oppression can arise under conditions where social groups are disadvantaged in the emergence of bargaining norms. As we show, intersectional disadvantage can arise even when actors from all social categories are completely identical in terms of preferences and abilities. The conditions necessary to derive such disadvantage are relatively minimal. And when actors behave in ways that reflect stronger intersectional identities, the potential for disadvantage increases.