Science is broken; let’s fix it. This has been my mantra for some years now, and today we are launching an initiative aimed squarely at one of science’s biggest problems. The problem is called publication bias or the file-drawer problem and it’s resulted in what some have called a replicability crisis.

I’ve started blogging at PsychFileDrawer. One of our first posts is addressed to the Association for Research in Personality newsletter: Regarding your article entitled “Personality Psychology Has a Serious Problem (And so Do Many Other Areas of Psychology)”, We agree wholeheartedly with your diagnosis of a major problem in publication practices in psychology.

The transmission of new scientific ideas and knowledge is needlessly slow: Flow slower Solution Journal subscription fees Open access mandates Competition to be first-to-publish motivates secrecy Open Science mandates Jargon Increase science communication;

Richard Feynman, in his 1974 cargo-cult science commencement address: Unfortunately, the average scientific journal article doesn’t follow this principle. I wouldn’t go so far as to say that the average article is just a sales job, but the emphasis is really on giving the information that favors the author’s theory.

How do you get on top of the literature associated with a controversial scientific topic? For many empirical issues, the science gives a conflicted picture. Like the role of sleep in memory consolidation, the effect of caffeine on cognitive function, or the best theory of a particular visual illusion. To form your own opinion, you’ll need to become familiar with many studies in the area.

First were the Climategate emails. There, Lack of transparency in climate data analyses and climate models contributed to the doubts of skeptics regarding climate change, and made it easier for the skeptics to convince the public that there is good reason for skepticism. Now, the Marc Hauser affair has cast a shadow across another sub-area of science. How can we prevent these scientific fiascos from occurring in the future?

To what extent should we have confidence in the average published scientific result? The news that Professor Marc Hauser of Harvard University may have been involved in scientific misconduct, yielding irreproducible results, prompts us to reflect on whether irreproducible results are usually caught, or not.

In writing scientific articles and grants, we find ourselves saying the same type of thing over and over again. We’re almost always talking about theories and evidence. We discuss the relationship of the evidence to the theories, saying whether particular evidence supports the theory or undermines it. To write well, we need to have lots of ways to say these things. So I’m making a list of the ways.

So I knew neuroscience has exploded over the last few decades, but I didn’t know its emergence as a more autonomous discipline is “the biggest structural change in scientific citation patterns over the past decade”. In the authors’ words that follow, they are referring to their figure showing neuroscience emerging as a new citation macro-cluster: “We also highlight the biggest structural change in scientific citation patterns over the past

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