Does Popularity Influence Reliability? An Introduction

Well hi there! Welcome to the next edition of “Papers in Meta Science” where I walk through interesting papers that use science to scrutinize science. During the first go around we looked at the John Ioannidis paper “Why Most Published Research Findings Are False”, and this time we’re going to look at a paper that attempted to prove one of that papers key assertions: that “hot” scientific fields produce less trustworthy results than less popular fields. This paper is called “Large-Scale Assessment of the Effect of Popularity on the Reliability of Research“, and was published on PlosOne by Pfeiffer and Hoffmann in 2009. They sought to test empirically whether or not this particular claim was true using the field of protein interactions.

Before we get to the good stuff though, I’d expect this series to have about 3 parts:

  1. The Introduction/Background. You’re reading this one right now.
  2. Methods and Results
  3. Further Discussion

Got it? Let’s go!

Introduction:  As I mentioned up front, one of the major goals of this paper was to confirm or refute the mathematical theory put forth by John Ioannidis that “hot” fields were more likely to produce erroneous results than those that were less popular. There are two basic theories as to why this could be the case:

  1. Popular fields create competition, and competitive teams are more likely to be incentivized to cut corners or do what it takes to get positive results (Ioannidis Corollary 5)
  2. Lots of teams working on a problem means lots of hypothesis testing, and lots of tested hypotheses means more false positives due to random chance (Ioannidis Corollary 6).

While Pfeiffer and Hoffman don’t claim to be able to differentiate between those two motives, they were hopeful that by looking at the evidence they could figure out if this effect was real and if it was perhaps estimate a magnitude. For their scrutiny, they chose the field of protein interactions in yeast.

This may seem a little counter-intuitive, as almost no definition of “popular science” conjures pictures of protein interactions. However, it is important to remember that the point of this paper was to examine scientific popularity, not mentions in the popular press. Since most of us probably already assume that getting headline grabbing research can cause it’s own set of bias problems, it’s interesting to consider a field that doesn’t grab headlines. Anyway, despite it’s failure to lead the 6 o’clock news, it turns out that the world of protein interactions actually does have a popularity issue. Some proteins and their corresponding genes are studied far more frequently than others, and this makes it a good field for examination. If a field like this can fall prey to the effect of multiple teams, than we can assume that more public oriented fields could as well.

Tune in next week to see what we find out!

2 thoughts on “Does Popularity Influence Reliability? An Introduction

  1. Pingback: Does Popularity Influence Reliability? Methods and Results | graph paper diaries

  2. Pingback: Stats in the News: February 2017 | graph paper diaries

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