On blog writing (and happy 1.5'ish year anniversary!)

I've been writing on this blog for about a year and a half. As with any milestone (ok, so I missed the anniversary of the first post by six months), this fact has put me in a reflective mood and I'm eager to analyze what I've learned from this endeavor.

My original intent for starting the blog was to have a place to jot down my ideas and sort them according to some logical framework. My mind was a discombobulated mess of tasks I had to do, dates I had to keep, and theories that intermingled to the extent that I had difficulties keeping them straight. Of course, I could always jot down notes in a notebook or journal (and I do), but I found that my handwriting simply couldn't keep up with the rate at which my thoughts crystallized into a pattern in my mind. Thus, I started the blog, but honestly did not care whether others read it.

My first post sums up this intent very well. (Having written it so long ago, it actually seems as if someone else wrote it.) So has the blog succeeded in this regard? I think so. I've certainly managed to find a broad range of topics on which to flesh out my thoughts, and my thinking is much more clear than when I started.

The most amazing thing I've found from writing, especially through this medium, is that my intent for a post almost always changes as I write it, leading me to discover something in the process. For example, I first started this post as a discussion on writing techniques, inspired by this article. I suspect that the reason for this is that the public nature of a blog impresses upon me the need to be logical. I dare not commit a logical fallacy in front of the entire digital world, especially since I purport to be a "scientist." So, as I place my thoughts into writing, I'm better able to catch errors in my thinking, fix them, and as a result find new conclusions and ideas.

For this reason I've recently come to appreciate the value of an audience. Sure, my readership is next to nil, but building one takes work that I simply have not put in. That's changing now. Through the magic of Google, I've discovered ways to attract any sort of attention possible popularize my blog, including http://www.twitterfeed.com. If more people are reading what I write, I'll probably pay closer attention to it.

And what of the future? Do I have any more hopes for my writing? Well, trying to keep a regular post schedule has been challenging, so I hope that I can maintain it. I also hope that, if enough people do start reading this blog, that I can gain a lot from comments. I realize my viewpoint is very particular in a large field. My biases likely keep me from conclusions that are just as valid but I otherwise discount or miss entirely.

This was actually a rather easy and fun post to write. If you do enjoy this blog, feel free to share it with your friends who might find it interesting. I'd appreciate it ;)

On a side note: thank you Google for changing the layout of the editing screen on Blogger. The newer, more professional look means I don't have to Alt-Tab to Matlab when my advisor enters my office unexpectedly.

I'm not the only one with these suspicions...

“I have known more people whose lives have been ruined by getting a Ph.D. in physics than by drugs.” - Dr. Jonathan Katz

This quote, by way of this article, is a bit distressing. Still, the article reaffirms several thoughts I've had recently about the prospects of obtaining a job in academia. Academia is simply too saturated with workers. This article is a great summary of some recent data and opinion pieces and I think should be read by anyone who is planning to obtain their PhD in a scientific field in the near future.

http://promega.wordpress.com/2011/08/26/the-ph-d-glut-do-we-have-too-many-ph-d-s/

When is a conclusion good enough?

I've been doing a lot of reading recently on modern probability theory, Bayesian analysis, and information theory. One of the central tenets of these theories is that any proposition has associated with it a degree of plausibility, i.e. a probability of being true, that reflects the amount of information available. The proposition, "the sky is blue" is extremely plausible since it is based off of daily self-observations and confirmed by others. As another example, I judge the proposition, "thirty million Americans have blue eyes" as plausible based on the knowledge of the current population of the United States and my own observations on the frequency of encountering blue-eyed people. However, this is not as likely to be true as the first statement.

A conclusion in a scientific paper is nothing more than a proposition and thus possesses its own degree of plausibility. The information available to the reader for determining the plausibility of the conclusion is the data presented in the paper and all previously published work on the same topic. Of course, other factors weigh in, such as prejudices for particular theories and affinities or dislikes for the authors on the paper. Temporarily placing these other factors aside, I wonder, "when does a conclusion possess a large enough degree of plausibility to be considered true?"

Of course, a definite answer doesn't exist. No scientific proposition can be true with 100% certainty and it is silly to think that we can even assign a threshold probability for evaluating a scientific paper's correctness. Just imagine a paper successfully passing through the peer-review process so long as it is evaluated to be 78.63% or more true by its reviewers. But the question remains relevant. Science is a culture and every culture has criteria by which it evaluates claims.

In a closely-related post I wrote about the fallacies that workers commit while evaluating other work. But I find it much more difficult to identify the criteria for establishing the truthfulness and quality* of research. Unfortunately, I don't think I'll be able to fulfill my full potential as a scientist until I am capable of doing so.

Note: The problem of defining quality has been approached at great length by American author Robert Pirsig in his popular novel "Zen and the Art of Motorcycle Maintenance." One of his primary arguments is that Quality is actually an undefined construct present at the seminal moment when an observation is made and processed by the brain. People may know if something possesses Quality, but it is inherently undefinable.

Why I like Dr. Ben Goldacre

I've been trying to keep my posts to once a week on Wednesdays, but sometimes I simply just want to share something interesting. In a recent Bad Science post, Dr. Ben Goldacre discussed sampling error in relation to unemployment figures in the UK. The article itself is interesting, but I found the description of systematic sampling error especially amusing:

Firstly, you’ll be familiar with the idea that a sample can be systematically unrepresentative: if you want to know about the health of the population as a whole, but you survey people in a GP waiting room, then you’re an idiot.

The great physicist Subrahmanyan Chandrasekhar gave a famous lecture at the International Symposium in Honor of Robert R. Wilson in April, 1979 entitled "Beauty and the Quest for Beauty in Science." In the second paragraph of the lecture, he quotes Poincaré:

The Scientist does not study nature because it is useful to do so. He studies it because he takes pleasure in it; and he takes pleasure in it because it is beautiful. If nature were not beautiful, it would not be worth knowing and life would not be worth living.... I mean the intimate beauty which comes from the harmonious order of its parts and which a pure intelligence can grasp....

It is because simplicity and vastness are both beautiful that we seek by preference simple facts and vast facts; that we take delight, now in following the giant courses of the stars, now in scrutinizing with a microscope that prodigious smallness which is also a vastness, and, now in seeking in geological ages the traces of the past that attracts us because of its remoteness.

Good science is not forced and does not evolve from long hours in the lab and a work-centric lifestyle alone, though I admit that these are necessary to maintain a healthy scientific career. Rather, science is intimately related to one of the most basic of human traits: the impassioned drive to create order out of chaos.

And this is why, despite my affection for Poincaré, I disagree with part of the above quote. Beauty does not exist within Nature because its parts are inherently balanced and "harmonious." Beauty exists as a result of the mind imparting its own structure to random titillations of the senses. Men and women do not render Nature meaningful through physical exertion alone. The reduction of Nature to coherent understanding is the realm of Science.

What a timely survey

Nature Jobs posted an article last week that summarizes the results of a survey conducted on graduate students in the sciences about their satisfaction with graduate school. Here are some of the more interesting points:

1. 78.8% of first year PhD students responded that they were "very" or "quite" likely to continue on to a university research position after graduate school.  In comparison 62% of fifth years answered the same.
2. Competition is the biggest factor in steering students away from academic careers.
3. 44.6% of students thought about post-school career options before entering graduate school.
4. 71.6% of European-based students reported that they were somewhat or very satisfied with their overall graduate school experience, compared to just 57.1% in the US and 62.3% in Japan.

This last point is interesting because I recently had a discussion about it with my advisor (who is Romanian). He claims that the reason for the significant difference between US and European students concerning the level of satisfaction with  their graduate studies is the perception of education in the two cultures. Education is held in high esteem in many European countries and professors carry a highly-valued social status.

In contrast, scientific jobs often carry a certain stigma with them in the US. Amusingly, I had a travel buddy--an engineer for an aerospace company--once explain to me what lengths he went to to hide the fact that he studied engineering when hitting on girls in college.

I'm not certain that being an intellectual is a turn-off, however. Consider the tech industry (Google, etc.) and the fairly well-received social status that its employees enjoy despite their aptitude for computers and technology. The real substance here is that they also enjoy good incomes and a stable job. So, the point is that intelligence is not socially undesirable; rather, it's that a good career and income is more highly valued.

The survey's findings seem to corroborate my recent conclusions about life as a graduate student. I must admit that I'm a little jealous of my engineer friends who went to work immediately after school. They're making much more money, have more free time, and are generally moving forward with their lives at a comfortable pace. And since we came from the same educational background, it's sometimes demoralizing to consider where I'm at with my life and find that I'm lagging them in these respects due to my role as a graduate student.

But I'll be damned if a job in industry can elicit the same oh-so-sweet feeling when an experiment works, the results fit neatly within the model, and one little mystery of nature finds itself tamed by my own cognitive exertions that is rewarded by a career in science.

What I wish I had known about academia (before I entered graduate school)

I'm entering my fifth year of graduate school this upcoming semester and, accordingly, have been increasingly thinking about my life afterward. Moments of reflection and talks with other students have revealed that there are a good number of things that I was unaware of concerning a career in academia when I began my graduate studies. Most of these things have taken me a long time to learn because the points were subtle or I was too naive to honestly assess the matter. Though these thoughts may not be true by the actual numbers (e. g. I haven't looked at the availability of teaching positions or the average income of post-docs), they certainly have found other voices, such as a few of the authors in this April Nature issue. And since the thought of a large number of people holds a good deal of influence regardless of its validity, I will take these thoughts to be true and offer them as advice to those who are considering a career in academia.

Career Point Number One: A career in academia—specifically in science—requires more hard work and dedication than most careers. This is due to a number of reasons, including a saturation of workers in the field, competition over resources, and a career trajectory that is difficult to advance through. Too many people within academia could be considered the cause of the competition over resources, but it's significant in its own right since it dilutes the quality of work being done. And as for a difficult career trajectory: a colleague told me the scariest thing one could do of all career moves is enter upon an assistant professorship with a family and mortgage with no guarantee of tenure.


CPN Two: Teaching positions are sparse (this was a surprise to me!). Many tenured professors or industry veterans enjoy retiring into academic teaching positions. There will not be much leverage for new graduates in obtaining a desired teaching position against those more experienced in the field.

CPN Three: No matter how amiable your advisor, it is not in their personal interest to graduate students. Losing experienced and knowledgeable students hurts their ability to publish, obtain funding, and generally proceed through their own academic career paths.

CPN Four: A post-doc may not be the best option for advancing a scientific/academic career. Many advisors interpret the post-doc role as one similar to a graduate student's but unencumbered by educational burdens such as attending class. A move to industry following graduation, however, may provide better networking opportunities and more chances to evolve one's professional skill set. One can always return to academia.

CP Five: One need not work in academia to retain one's interest in science. This was in no way obvious to me from the start. After having identified my interest in physics, I proceeded through my education with the idea that physics would be my career. But herein lies the most important distinction of all: science is not a career.

Science is the pursuit of truth and the delight in discovering new things through experimentation. It need not be grand in scale or require a large amount of resources. It is an unfortunate development that a career in academia and science have assumed the same position in most people's minds.

I admit that this assessment may appear a bit bleak at first, but for me it is rather liberating. I'm OK finding a career that is not centered squarely within academia because the requirements of such a job are too demanding given my other interests. This in no way means that my life or work can not contribute significantly to science. But to conclude that academia alone is the only way to significantly impact science is to commit a fallacy that could launch one onto a difficult and unsatisfying career path.