JBJC Day -1

According to some of my intel, I should have 'Net access for much of this trip. So I'll be trying a little reportage on this meeting.

Currently in the McAllen airport waiting to fly to Houston. McAllen has free internet; :)Houston makes you pay. :(

The talk is as ready as it's going to be. Fortunately, I can practice on the long flight to San Diego on my Pocket PC. I remembered to copy the talk over to it... Whew!

California dreamin'... I wish

Didn't sleep well last night. Don't expect to sleep well tonight. I'm getting on a plane later today and going to San Diego for the annual meetings of the J.B. Johnston Club and the Society for Neuroscience.

I'm giving a talk at the J.B. Johnston Club, and the talk was not at the point I wanted it to be last night. So I was having a bit of a freak-out trying to get it to where I wanted it to be. I'm almost there, but a couple of practice runs are needed to be sure.

And there are so many things I wanted to do before I left that are not done.

On the plus side... someone read one of my papers! And cited it!

One of the nice things about living in the digital age is that lots of things can be done automatically. Many journals offer "Citation alerts" that send you an email when a particular paper has been referenced in another journal. Yesterday, I got my very first one! And the best part was.. it was by someone that I personally do not know. It's very easy in this business sometimes to think that the only people who have looked at your stuff are people that you have actually met, so small is this community.

And even better was that the paper was actually relevant to some other projects I'm currently doing.

Right. Time to continue panicking for conference trip.

And the suck factor goes up again

Damnit damnit damnit damnit!

I just discovered that an abstract I submitted for an upcoming meeting has a typo in it. In the title. In the species name.

Once, this probably wouldn't have mattered so much. But now, since this is being published, it means that people who are searching for papers on that species through Google or something won't find it.

This alone does not prove that I suck. What proves that I suck is that this is the second frickin' time I've done this.

Mad at myself now.

Denied!

Forgot to mention something from Monday.

Various funding agencies have limited submission programs: they only accept a set number of proposals from an institution. So, when more people want to submit proposals than there are slots available, there has to be some mechanism to sort out who will submit.

So I had submitted an internal preproposal for one of these limited submission grants. Previously, we had our Dean review these and decide. This year, for the first time, for reasons I don't entirely understand, instead of just reading the preproposal (which was about 5 pages, if I remember right), they formed this little committee to review the preproposals, and asked the authors (like me) to come in and give a presentation justifying our preproposal.

I spent several hours working on a little song and dance for this.

Since you read the title for this entry, you know I got turned down.

At this point, I am not convinced that this new review mechanism adds any value to the submission process. It just seems to eat up more time.

Weather watching

The fires around San Diego are really scary. But according to the Society for Neuroscience, the show is going on. I expect the air quality to be atrocious, but if that the biggest problem I personally have, I reckon I have nothing to complain about and a lot to be thankful for. I've been putting a fair amount of time tweaking my talk for the J.B. Johnston Club over the last couple of days, which I'll be attending right before the Neuroscience meeting. Unfortunately, a few other things are going way on the back burner.

Ugh. No pun intended.

Fire

I'm supposed to got to San Diego in 8 days for the Society for Neuroscience meeting.

Today, I start seeing headlines like this:

Half a million flee California wildfires

President declares emergency as wildfires continue to rage unchecked across drought-struck region.

It's going to be an interesting week.

Time tricks

I was gone to Texas A&M for less than 48 hours, but I feel like I've been gone the better part of a week. Weird.

I really enjoyed the trip. A&M is very, very different than any other uni I've visited in some ways. I haven't been on another campus where I've seen people standing around handing out bibles in the middle of campus, or any place with so many cadets with crew cuts and knee high boots.

Met several very nice scientists, and I think my talk went well. Had lunch at the Dixie Chicken, which has atmosphere to spare and good pub grub. Dinner was at The Republic, which had excellent steak and what I called "the schizophrenic desert" – a key line cheesecake / creme brule combo, that worked unexpectedly well.

Mike Smotherman, you rock! Thanks for the invite!

Aggieland

I'm in College Station tonight. Tomorrow, I'm giving a guest seminar at Texas A&M University. A&M was just named best university in the U.S. by The Washington Monthly and which has a football stadium that may be visible from low Earth orbit.

Last night, my talk was not in a state I was happy with, and I did not sleep well because of it. Tonight, I'm still terrified / intimidated, but the talk is in much better shape. And I've had a hot bath to help me relax. So I hope for a good night's sleep.

Just a snapshot from walking home

Learning curves

I was thinking about something this morning, and I thought of the saying that something has "a steep learning curve." I started thinking about graphs showing learning.

And realized what a stupid expression that was.

The term "learning curve" comes from psychology. Typically, you plot time on the X axis on the bottom and proficiency (or accuracy, performance, percent correct, or what have you) on the Y axis on the right.

The typical learning pattern is much different from the graph I sketched up for this blog post. Usually, people improve quickly with very little practice, and then it gets harder to get better. The graph I drew goes in the reverse pattern, but it doesn't matter to the point at hand.

When you're getting better at something quickly, the graph shoots up at a steep incline. The closer to vertical, the faster you're learning.

So when you say something is hard to learn, you should really say that thing has a shallow learning curve, not a steep one.

It's strange that I've studied learning and behaviour and such for years, and have used the cliché "steep learning curve" meaning hard for years, but never put the two together until this morning.

Of course, other people have beat me to this realization. But at least I arrived at the insight through my own independent thinking.