I confess that I am an experiment chauvinist – I look down on studies that are purely observational, studies that don’t manipulate anything. Where does my prejudice come from? One factor is that as a perceptual and cognitive psychologist, when I do science, I’m usually interested in the causes, or underlying mechanisms, of a phenomenon.

To evaluate and build on previous findings, a researcher sometimes needs to know exactly what was done before. Computational reproducibility is the ability to take the raw data from a study and re-analyze it to reproduce the final results, including the statistics.

In a clever bit of rhetoric, Professor Dorothy Bishop came up with “the four horsemen of irreproducibility“: publication bias, low statistical power, p-hacking, and HARKing. In an attempt at more complete coverage of the causes of the replication crisis, here I’m expanding on Dorothy’s four horsemen by adding two more causes, and using different wording. This gives me six P’s of the replication crisis!

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.

Scientists of all sorts increasingly recognize the existence of systemic problems in science, and that as a consequence of these problems we cannot trust the results we read in journal articles. One of the biggest problems is the file-drawer problem. Indeed, it is mostly as a consequence of the file-drawer problem that in many areas most published findings are false. Consider cancer preclinical bench research, just as an example.

Below are research presentations I’m involved in for Vision Sciences Society in May. If you’re attending VSS, don’t forget about the Publishing, Open Access, and Open Science satellite which will be Friday at 11am.

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;

I recently learned that a journal called Obesity Reviews has a “Fast Track Facility”: This is a terrible development for academia. It creates a two-tier system, wherein scientists who are well-funded such as those from rich countries now have an unfair advantage over those who don’t. Science traditionally has been a partial refuge from the injustice of rich vs. poor.

Previously, the Australian Research Council (ARC) expressly forbade use of grant funds to pay publication charges. This prevented many of us from publishing in open-access journals, as they generally charge a fee. Fortunately, the newly-revised funding rules change that, and instead strongly encourage open access, via journals and via depositing one’s research in an institutional repository. Hooray!

A new article in the New York Times regarding the allegations against Marc Hauser illustrate how difficult it is to determine whether one is guilty of scientific fraud. A main problem is that record-keeping standards are so lax. This is another reason why open science is important. Open science involves releasing original data and analyses, which is much easier if you have been keeping good records along the way.