[TreesAndBirds]

Excellent post that summarizes better than I could what matters in all this. It's untenable for him to be an example of scientific leadership and it's baffling to me that apparently most of the BOT doesn't grasp that.

I guess my reaction is a bit different. Does anybody seriously believe that the senior author on the vast majority of scientific publications has verified the provenance of all (actually any of) the data contained therein? They are not in the lab physically watching all the experiments that are done. In many cases they are collaborating with colleagues that are not even at the same institution. Some of the larger labs have 70 or 80 graduate students who are working under supervision of post-docs that the PI actually doesn't know all that well. While some may operate in the fantasy world where all the PIs are intimately involved in every experiment and actually know what is going on in all aspects of their labs, that is simply not how it is. I think in many cases the best one can hope for is that the PI has actually read the paper before it was submitted :-).

It isn't a good system in many ways, but it is the system we have. It relies on the honesty of a lot of people. In point of fact, artifacts are sometimes the basis of some paper's data. There are so many papers published that contain data that will never be important enough to reproduce that many such thing go unnoticed for years. I think there are probably more honest errors than fraud. How many papers are published that are the result of something finally "working" after many failures? How many PIs insist on the data being reliably reproducible?

I know virtually nothing about how university research is conducted. But I do know that culture and values are set at the top. Signals are sent, sometimes subtlely, sometimes not, about what is most important in an organization or group. Things like profitability, meeting deadlines and carefulness/quality are often in conflict in the business world. The leader sets the tone on what to prioritize. Yes, the leader can not know everything that more junior people or colleagues are doing, but with the right messaging it seems unlikely that a disproportionate number of these errors would occur (assuming they were disproportionate). I have no view on whether anything was intentional, or whether MTL should have been more careful in reviewing these papers, but as President of a university setting the right culture and expectations is really important, and Im concerned that MTL has demonstrated weakness in that area.

[TreesAndBirds]

Excellent post that summarizes better than I could what matters in all this. It's untenable for him to be an example of scientific leadership and it's baffling to me that apparently most of the BOT doesn't grasp that.

I guess my reaction is a bit different. Does anybody seriously believe that the senior author on the vast majority of scientific publications has verified the provenance of all (actually any of) the data contained therein? They are not in the lab physically watching all the experiments that are done. In many cases they are collaborating with colleagues that are not even at the same institution. Some of the larger labs have 70 or 80 graduate students who are working under supervision of post-docs that the PI actually doesn't know all that well. While some may operate in the fantasy world where all the PIs are intimately involved in every experiment and actually know what is going on in all aspects of their labs, that is simply not how it is. I think in many cases the best one can hope for is that the PI has actually read the paper before it was submitted :-).

It isn't a good system in many ways, but it is the system we have. It relies on the honesty of a lot of people. In point of fact, artifacts are sometimes the basis of some paper's data. There are so many papers published that contain data that will never be important enough to reproduce that many such thing go unnoticed for years. I think there are probably more honest errors than fraud. How many papers are published that are the result of something finally "working" after many failures? How many PIs insist on the data being reliably reproducible?

I know virtually nothing about how university research is conducted. But I do know that culture and values are set at the top. Signals are sent, sometimes subtlely, sometimes not, about what is most important in an organization or group. Things like profitability, meeting deadlines and carefulness/quality are often in conflict in the business world. The leader sets the tone on what to prioritize. Yes, the leader can not know everything that more junior people or colleagues are doing, but with the right messaging it seems unlikely that a disproportionate number of these errors would occur (assuming they were disproportionate). I have no view on whether anything was intentional, or whether MTL should have been more careful in reviewing these papers, but as President of a university setting the right culture and expectations is really important, and Im concerned that MTL has demonstrated weakness in that area.