(Comment by me on a post at Women in Wetlands.)
The original post is interesting and thought provoking, and I encourage you to read it. It dealt with "...the idea that successful scientists are somehow luckier than everyone else." The post makes the assertion that "This is rarely true..." The text below is my response.
Interesting post. I want to completely agree with you, but recent life experiences (graduate school) make me disagree.
It's not that I think successful scientists don't work hard. I know many very successful scientists, and they definitely work very hard. No question. And they're smart. No question. The problem is that I also know many scientists who are also very smart and work very hard but just haven't obtained success. So, what's the difference?
The difference must either be "luck" or some je ne sais quoi traits the successful have and the unsuccessful do not. And, I think it's both.
I'd like to give a concrete example to illustrate. Let's say a smart, hard-working student starts graduate school. The student chooses to do research in a brand new lab with a brand new PI. This choice is risky, since the lab and the PI are unknowns, but with risk often comes the possiblity of high reward. The reward might be learning to build an experiment and a lab from scratch with an enthusiastic, rising-star PI.
But, sometimes a new PI will flounder, and it's impossible for this floundering to not greatly affect the students. Perhaps the PI can't obtain funding after start-up funds run out. And students are left to try to join a new lab 5+ years in, or try to graduate with no publications. Or perhaps the PI's experiments, which sound amazing enough to be funded by brilliant, experienced professors sitting on NIH panels, turn out to be impossible to interpret. And students are left with uninterpretable results, no publications, and really no results that would even make a reasonable thesis. Should the students have been smart enough to avoid a new PI? Or smart enough to avoid a bad new PI? Even the talented and experienced professors who chose to hire the new PI weren't smart enough to avoid the bad PI, so it seems impossible to expect students to be able to discern. So, the student who chose this lab is highly unsuccessful by the standards used for judging success in science. The student possibly receives no Ph.D., or maybe a Ph.D. with no publications. Was that student less talented? Less hard working? No. That student was unlucky.
Could that student have possessed some traits that would have prevented this "unlucky" situation? Yes. The student could have not been a risk-taker, and therefore not chosen a new lab and new PI. Or the student could be non-persistent, and could have chosen to switch labs after 2-3 years of frustration. So, this situation selected for non-risk-taking quitters. Just what we want in science, no?
I suppose the biggest argument would be, could that student still go on to achieve success? Maybe. Maybe that student can try to do a brand new Ph.D. using everything they know now. Or maybe the student can do multiple post docs. But maybe now that student is 28-30 years old, and doesn't feel they have the time or energy to do it all again. Plus, now they know it's not all about hard work and talent. Now they know there's luck involved, and no guarantee that they won't be unlucky again, perhaps in a different way this time.
I actually think this last issue is the worst negative impact of the whole situation. As you say, believing luck has anything to do with success is self-defeating. But isn't it also self-defeating to just decide you're not cut out for this profession because your hardest work wasn't good enough in this particular situation?
Wednesday, March 17, 2010
Tuesday, March 16, 2010
How to Get a PhD (in science, anyway) - Step 9
Step 9: Write the thesis.
If you have written one or more publications, with minor modifications you likely already have one or more thesis chapters. Go back to your rough thesis outline and fill it in with the methods you used and the results you have now. Write it similarly to the papers, starting with the rough outline, filling in rough drawn versions of figures, replacing drawn figures with preliminary versions of real figures, writing subsection outlines. Decide on any gaps that you'd like to fill. Fill in text - figure captions, introduction, abstract, text, references, acknowledgements, conclusions. Edit and reedit. Keep track of methods, data, and analysis used in the thesis. Submit to committee, defend, and graduate.
If you have written one or more publications, with minor modifications you likely already have one or more thesis chapters. Go back to your rough thesis outline and fill it in with the methods you used and the results you have now. Write it similarly to the papers, starting with the rough outline, filling in rough drawn versions of figures, replacing drawn figures with preliminary versions of real figures, writing subsection outlines. Decide on any gaps that you'd like to fill. Fill in text - figure captions, introduction, abstract, text, references, acknowledgements, conclusions. Edit and reedit. Keep track of methods, data, and analysis used in the thesis. Submit to committee, defend, and graduate.
How to Get a PhD (in science, anyway) - Step 8
Step 8: Decide. Write the thesis or keep going?
Do you have enough for a thesis? Do you have as much as you want/need before you move on to your next job? Can you convince your advisor to let you go or stay, as you wish? Make a decision and repeat previous steps as necessary.
Do you have enough for a thesis? Do you have as much as you want/need before you move on to your next job? Can you convince your advisor to let you go or stay, as you wish? Make a decision and repeat previous steps as necessary.
How to Get a PhD (in science, anyway) - Step 7
Step 7: Publish.
Once you have an interesting set of results, write it up and publish it. Think about the appropriate journal for the paper. Look at where many of your references are published, and consider the novelty of your work. Then, start with your drawn up picture outline and modify it to fit into the journal's format. Fill in the drawn figures with preliminary versions of real figures. Make a real paper outline with an introduction, methods, results, and conclusions. Do you notice any gaps as you go? Any logical gaps? Any control experiments that need to be performed? Any tests of accuracy or precision that need to be performed? Any uncertainties to be quantified? Plan and perform more experiments as needed. Fill in figure captions, the abstract, and other text, including references. Get feedback from your advisor and coauthors. Edit and reedit and reedit. Perfect figures. Carefully keep track of methods, data, and analysis used in the paper. Submit and wait for your response!
Once you have an interesting set of results, write it up and publish it. Think about the appropriate journal for the paper. Look at where many of your references are published, and consider the novelty of your work. Then, start with your drawn up picture outline and modify it to fit into the journal's format. Fill in the drawn figures with preliminary versions of real figures. Make a real paper outline with an introduction, methods, results, and conclusions. Do you notice any gaps as you go? Any logical gaps? Any control experiments that need to be performed? Any tests of accuracy or precision that need to be performed? Any uncertainties to be quantified? Plan and perform more experiments as needed. Fill in figure captions, the abstract, and other text, including references. Get feedback from your advisor and coauthors. Edit and reedit and reedit. Perfect figures. Carefully keep track of methods, data, and analysis used in the paper. Submit and wait for your response!
How to Get a PhD (in science, anyway) - Step 6
Step 6: Keep going.
Keep reading, discussing, critiquing, planning. Update the picture outline for your paper on a monthly basis, or as your results make a new outline necessary. Keep conducting your experiments, collecting and analyzing your data, and interpreting your results. And keep writing in your lab notebook.
Keep reading, discussing, critiquing, planning. Update the picture outline for your paper on a monthly basis, or as your results make a new outline necessary. Keep conducting your experiments, collecting and analyzing your data, and interpreting your results. And keep writing in your lab notebook.
How to Get a PhD (in science, anyway) - Step 5
Step 5: Start your research and finish up coursework and exams as you can.
*Read.
Get acquainted with your specific research topic and techniques. Start with the most recent review articles on your topic, and work into more specific literature. Read grant proposals if available from your advisor.
*Discuss and critique the literature.
Ideally, discuss literature with colleagues and your advisor. A journal club where someone presents an article and everyone reads and critiques the article can be great for learning an article in depth and learning to critique the literature.
*Plan your research.
From the literature you've read, you should have been able to form some interesting and unproven hypotheses. Plan experiments to test your hypotheses. Plan experiments that will have interpretable results. Avoid experiments that will only be interpretable if your hypothesis is true. Also, ideally design experiments that utilize techniques that are already working in your lab. Don't underestimate the difficulty of developing a technique from the literature into a working technique in your lab. And remember that redoing something from the literature will get you no credit towards a thesis or a publication. Get as much feedback as possible during these planning stages. A good advisor or colleague can provide excellent perspective and ideas on what hypotheses are interesting to pursue, what experiments are more interpretable, and information about existing techniques and their difficulty.
*Make a super-rough, super-early thesis outline.
This outline is really just to focus your work. The thesis will generally consist of an Introduction, Methods Chapter, 2 or more Results Chapters, and Conclusions and References. Coming up with basic topics for your 2 results chapters will help you be focused and driven towards the ultimate Ph.D. requirement - the dissertation. And getting feedback from your advisor on this outline will help the two of you be on the same page from the beginning. Don't be too attached to this thesis outline, since you are only beginning to test your hypothesis, and want to be led to the most interesting possible research by your experiments.
*Make a super-rough picture outline for a paper.
Simply sit down for an hour and rough out drawings of figures you envision being in a paper. Figures often start with an experimental geometry figure, followed by the key results from your experiments. These results may be in the form of photographs, tables, graphs, or other forms of presenting results. Sometimes papers also include figures explaining key interpretations or models drawn from the results. Roughly draw figures you envision for your paper. Again, don't be too attached to this picture outline! Your experiments will yield the results, and these may lead you to different conclusions and down different paths than you expected. Again, feedback on this picture outline helps to get you and your advisor on the same page for expectations.
*Conduct your experiments, collect and analyze your data, and interpret your results.Plan on the long, intermediate, and short time scales. Make a very rough long-term plan that includes time frames for your planned experiments, analysis, and writing up the results as a paper. This long-term plan must be flexible to incorporate the findings of your day-to-day experiments. Plan on the intermediate-scale, e.g. the weekly time-scale. Choose which days to do which experiments, how much time must be set-aside for analysis, and remember to include time for keeping up with the literature, going to interesting talks, and planning. Plan on the short-time scale, i.e. for the experiment for the day.
*Write.
In your lab notebook, each day (or the previous evening), write down a goal or goals for the day, and an explanation of the planned methods. Write down and record as much as possible during the day, and close each day with some conclusions drawn from the day. For repetitive tasks with minimal changes, reference a previous page in the notebook, and/or type a template that can be printed and pasted into the notebook. Computer files are excellent resources, but be very careful about noting in your lab notebook where the files can be found. Also be very careful about backing up files, and remember that computer files are very easily changed. This easy changing is good and bad. The easy changes are good for updating files as new information is available, but bad if you need to reference what existed at a certain time. For example, a computer file holding a Methods procedure may be referenced in your lab notebook. Later, you may improve the procedure and update the computer file. But you may still need to know exactly how you performed the procedure for the data in your lab notebook. So, be careful with computer files and develop a system for updating and keeping old copies, and for backing up your files.
*Read.
Get acquainted with your specific research topic and techniques. Start with the most recent review articles on your topic, and work into more specific literature. Read grant proposals if available from your advisor.
*Discuss and critique the literature.
Ideally, discuss literature with colleagues and your advisor. A journal club where someone presents an article and everyone reads and critiques the article can be great for learning an article in depth and learning to critique the literature.
*Plan your research.
From the literature you've read, you should have been able to form some interesting and unproven hypotheses. Plan experiments to test your hypotheses. Plan experiments that will have interpretable results. Avoid experiments that will only be interpretable if your hypothesis is true. Also, ideally design experiments that utilize techniques that are already working in your lab. Don't underestimate the difficulty of developing a technique from the literature into a working technique in your lab. And remember that redoing something from the literature will get you no credit towards a thesis or a publication. Get as much feedback as possible during these planning stages. A good advisor or colleague can provide excellent perspective and ideas on what hypotheses are interesting to pursue, what experiments are more interpretable, and information about existing techniques and their difficulty.
*Make a super-rough, super-early thesis outline.
This outline is really just to focus your work. The thesis will generally consist of an Introduction, Methods Chapter, 2 or more Results Chapters, and Conclusions and References. Coming up with basic topics for your 2 results chapters will help you be focused and driven towards the ultimate Ph.D. requirement - the dissertation. And getting feedback from your advisor on this outline will help the two of you be on the same page from the beginning. Don't be too attached to this thesis outline, since you are only beginning to test your hypothesis, and want to be led to the most interesting possible research by your experiments.
*Make a super-rough picture outline for a paper.
Simply sit down for an hour and rough out drawings of figures you envision being in a paper. Figures often start with an experimental geometry figure, followed by the key results from your experiments. These results may be in the form of photographs, tables, graphs, or other forms of presenting results. Sometimes papers also include figures explaining key interpretations or models drawn from the results. Roughly draw figures you envision for your paper. Again, don't be too attached to this picture outline! Your experiments will yield the results, and these may lead you to different conclusions and down different paths than you expected. Again, feedback on this picture outline helps to get you and your advisor on the same page for expectations.
*Conduct your experiments, collect and analyze your data, and interpret your results.Plan on the long, intermediate, and short time scales. Make a very rough long-term plan that includes time frames for your planned experiments, analysis, and writing up the results as a paper. This long-term plan must be flexible to incorporate the findings of your day-to-day experiments. Plan on the intermediate-scale, e.g. the weekly time-scale. Choose which days to do which experiments, how much time must be set-aside for analysis, and remember to include time for keeping up with the literature, going to interesting talks, and planning. Plan on the short-time scale, i.e. for the experiment for the day.
*Write.
In your lab notebook, each day (or the previous evening), write down a goal or goals for the day, and an explanation of the planned methods. Write down and record as much as possible during the day, and close each day with some conclusions drawn from the day. For repetitive tasks with minimal changes, reference a previous page in the notebook, and/or type a template that can be printed and pasted into the notebook. Computer files are excellent resources, but be very careful about noting in your lab notebook where the files can be found. Also be very careful about backing up files, and remember that computer files are very easily changed. This easy changing is good and bad. The easy changes are good for updating files as new information is available, but bad if you need to reference what existed at a certain time. For example, a computer file holding a Methods procedure may be referenced in your lab notebook. Later, you may improve the procedure and update the computer file. But you may still need to know exactly how you performed the procedure for the data in your lab notebook. So, be careful with computer files and develop a system for updating and keeping old copies, and for backing up your files.
How to Get a PhD (in science, anyway) - Step 4
Step 4: Begin to complete requirements (coursework, exams) and look for a research group, topic and advisor.
Complete general requirements first, unless courses may help you choose your research topic.
Your advisor matters even more than the topic. Choose carefully. An amazing research subject and project can be ruined by a terrible advisor. The support of your advisor will be huge deciding factor on your Ph.D. and future career. Ideally, choose someone who truly wants to and knows how to support Ph.D. students through a successful Ph.D.
Complete general requirements first, unless courses may help you choose your research topic.
Your advisor matters even more than the topic. Choose carefully. An amazing research subject and project can be ruined by a terrible advisor. The support of your advisor will be huge deciding factor on your Ph.D. and future career. Ideally, choose someone who truly wants to and knows how to support Ph.D. students through a successful Ph.D.
How to Get a PhD (in science, anyway) - Step 3
Step 3: Start!
The curriculum - print it out when you start and put it in a file. That way, you have all the requirements in one place when you need to look it up again, and you have all the rules that existed when you started in case requirements change during your degree. You may also want to print requirements for Masters degrees. Why? What if you love your coursework and hate research? Do you really want to spend 5-10 years working on research you hate to perfectly prepare you to do more research you hate? No. Or what if you realize a completely different calling 2 years into your degree? Or what if you get a fantastic job offer, or want to/need to move across the country? You want to know your options if you realize the Ph.D. is not for you.
Requirements to print and keep on file:
Required coursework - specific classes, possible electives
Required exams - Qualifying, Comprehensive, Oral, Written, Proposals, Defense
Other requirements - publications, registration, thesis requirements
Committee requirements, time limits
The curriculum - print it out when you start and put it in a file. That way, you have all the requirements in one place when you need to look it up again, and you have all the rules that existed when you started in case requirements change during your degree. You may also want to print requirements for Masters degrees. Why? What if you love your coursework and hate research? Do you really want to spend 5-10 years working on research you hate to perfectly prepare you to do more research you hate? No. Or what if you realize a completely different calling 2 years into your degree? Or what if you get a fantastic job offer, or want to/need to move across the country? You want to know your options if you realize the Ph.D. is not for you.
Requirements to print and keep on file:
Required coursework - specific classes, possible electives
Required exams - Qualifying, Comprehensive, Oral, Written, Proposals, Defense
Other requirements - publications, registration, thesis requirements
Committee requirements, time limits
How to Get a PhD (in science, anyway) - Step 2
Step 2: Apply
Exams - General and Subject GRE's
Personal Statement
Recommendations
Exams - General and Subject GRE's
Personal Statement
Recommendations
How to Get a PhD (in science, anyway) - Step 1
Step 1: Choose a program
Location, School, Department, Faculty, Available research possibilities
Location, School, Department, Faculty, Available research possibilities
Tuesday, March 9, 2010
Humanities vs Science
(A comment by me on an FSP post)
...From discussions with academics in humanities, the demands, pressures, and everyday lives of humanities and science academics are very different. For one thing, it seems much more difficult to get a paying job in the humanities (as a grad student, as a professor, or as anything else.)
The student-professor relationship also seems very different. Students who work as research assistants in humanities seem to get paid, but get no credit on publications for which they assist? And students' research may have very, very little to do with their advisors' research. In contrast, Ph.D. advisors in the sciences seem to have huge responsibility to their students, often providing funding, lab space and equipment, the big idea behind the projects, and various degrees of involvement in their students' research process. All that responsibility is in exchange for co-authorship on publications, which seems to be the main determining factor on tenure decisions for all academics.
It seems like science professors are more managers and project leaders, while humanities professors continue more directly doing research and writing. That difference is much larger than just the disparity of the fields.
And there's also the difference that in science, researchers have to conceive of an idea that is interesting and not already published, design and build instrumentation to test said idea, acquire data (which may or may not provide interestingly interpretable results, and then analyze, interpret and publish said results. In the humanities, researchers get to skip right from conceive of an idea to the analysis. And they never have to worry that it just won't work. Effing science.
...From discussions with academics in humanities, the demands, pressures, and everyday lives of humanities and science academics are very different. For one thing, it seems much more difficult to get a paying job in the humanities (as a grad student, as a professor, or as anything else.)
The student-professor relationship also seems very different. Students who work as research assistants in humanities seem to get paid, but get no credit on publications for which they assist? And students' research may have very, very little to do with their advisors' research. In contrast, Ph.D. advisors in the sciences seem to have huge responsibility to their students, often providing funding, lab space and equipment, the big idea behind the projects, and various degrees of involvement in their students' research process. All that responsibility is in exchange for co-authorship on publications, which seems to be the main determining factor on tenure decisions for all academics.
It seems like science professors are more managers and project leaders, while humanities professors continue more directly doing research and writing. That difference is much larger than just the disparity of the fields.
And there's also the difference that in science, researchers have to conceive of an idea that is interesting and not already published, design and build instrumentation to test said idea, acquire data (which may or may not provide interestingly interpretable results, and then analyze, interpret and publish said results. In the humanities, researchers get to skip right from conceive of an idea to the analysis. And they never have to worry that it just won't work. Effing science.
Monday, March 8, 2010
"Success" in research training - NIGMS Question 1
1. What constitutes "success" in biomedical research training from the perspectives of an individual trainee, an institution, and society?
From the perspective of the individual, institution, and society, successful research training at the Ph.D. and postdoctoral level should prepare trainees to successfully lead research projects. Thus, trainees should develop and practice all aspects of the research process: project conception, design, and funding (including grant writing); experimental technique (ideally multiple techniques), data collection, and analysis; and interpretation, publication, and presentation of results. Many of these steps in the research process require critical evaluation of the relevant literature. In practice, research training is not complete without safety training, an emphasis on ethics, and knowledge of the rules governing research (such as government and institutional regulations). Trainees should be mentored in all of these skills, and should be given the opportunity to practice and develop these skills during their training.
The requirements for training at the Ph.D. and postdoctoral level are distinct from training for undergraduates or technicians. Undergraduates and technicians may only need training in the technical aspects of research, e.g. experimental techniques, data collection, and analysis. Many undergraduates and technicians may also benefit from the other aspects of training, but Ph.D. and postdoctoral level training demand the other aspects in order to educate trainees to the level of research project leadership.
Having research training completed in the most efficient manner is highly desirable. Efficient training makes a trainee capable of better work faster, which makes for more efficient use of funding, and more efficient use of the trainees time and opportunity costs incurred while training. Efficient training requires a careful and customized balance between guidance and independence. Too much guidance and a trainee may not learn to perform tasks independently; not enough guidance and a trainee may flounder unnecessarily. The efficiency of training is critical to creating excellent scientists without wasting time and money.
Finally, successful training also should include guidance for obtaining a post-training position. Guidance should give the trainee awareness of the types of positions for which they qualify, should help the trainee establish a professional network during training, and should provide evaluations of the trainee to help them choose the right post-graduate positions to pursue. Training should also ideally yield fair metrics for employers to use in judging trainees fit for post-training positions.
In summary, successful research training for Ph.D. and postdoctoral trainees should efficiently guide them through the practice of all aspects of the research process, and should also guide them in choosing their ideal post-training position.
From the perspective of the individual, institution, and society, successful research training at the Ph.D. and postdoctoral level should prepare trainees to successfully lead research projects. Thus, trainees should develop and practice all aspects of the research process: project conception, design, and funding (including grant writing); experimental technique (ideally multiple techniques), data collection, and analysis; and interpretation, publication, and presentation of results. Many of these steps in the research process require critical evaluation of the relevant literature. In practice, research training is not complete without safety training, an emphasis on ethics, and knowledge of the rules governing research (such as government and institutional regulations). Trainees should be mentored in all of these skills, and should be given the opportunity to practice and develop these skills during their training.
The requirements for training at the Ph.D. and postdoctoral level are distinct from training for undergraduates or technicians. Undergraduates and technicians may only need training in the technical aspects of research, e.g. experimental techniques, data collection, and analysis. Many undergraduates and technicians may also benefit from the other aspects of training, but Ph.D. and postdoctoral level training demand the other aspects in order to educate trainees to the level of research project leadership.
Having research training completed in the most efficient manner is highly desirable. Efficient training makes a trainee capable of better work faster, which makes for more efficient use of funding, and more efficient use of the trainees time and opportunity costs incurred while training. Efficient training requires a careful and customized balance between guidance and independence. Too much guidance and a trainee may not learn to perform tasks independently; not enough guidance and a trainee may flounder unnecessarily. The efficiency of training is critical to creating excellent scientists without wasting time and money.
Finally, successful training also should include guidance for obtaining a post-training position. Guidance should give the trainee awareness of the types of positions for which they qualify, should help the trainee establish a professional network during training, and should provide evaluations of the trainee to help them choose the right post-graduate positions to pursue. Training should also ideally yield fair metrics for employers to use in judging trainees fit for post-training positions.
In summary, successful research training for Ph.D. and postdoctoral trainees should efficiently guide them through the practice of all aspects of the research process, and should also guide them in choosing their ideal post-training position.
Thursday, March 4, 2010
NIGMS Strategic Plan for Training and Career Development
Ahhh...a chance to provide some feedback that may actually make a difference. Fellow scientists, let's help make things better for the next generation of trainees.
NIGMS Strategic Plan for Training and Career Development
They would like input to answer the following 7 questions:
1. What constitutes "success" in biomedical research training from the perspectives of an individual trainee, an institution, and society?
2. What can NIGMS do to encourage an optimal balance of breadth and depth in research training?
3. What can NIGMS do to encourage an appropriate balance between research productivity and successful outcomes for the mentor’s trainees?
4. What can NIGMS do through its training programs to promote and encourage greater diversity in the biomedical research workforce?
5. Recognizing that students have different career goals and interests, should NIGMS encourage greater flexibility in training, and if so, how?
6. What should NIGMS do to ensure that institutions monitor, measure, and continuously improve the quality of their training efforts?
7. Do you have other comments or recommendations regarding NIGMS-sponsored training?
My plan: Use my blog to write some thoughtful answers over the next few days, and then submit my input to their website. Anybody else want to play?
NIGMS Strategic Plan for Training and Career Development
They would like input to answer the following 7 questions:
1. What constitutes "success" in biomedical research training from the perspectives of an individual trainee, an institution, and society?
2. What can NIGMS do to encourage an optimal balance of breadth and depth in research training?
3. What can NIGMS do to encourage an appropriate balance between research productivity and successful outcomes for the mentor’s trainees?
4. What can NIGMS do through its training programs to promote and encourage greater diversity in the biomedical research workforce?
5. Recognizing that students have different career goals and interests, should NIGMS encourage greater flexibility in training, and if so, how?
6. What should NIGMS do to ensure that institutions monitor, measure, and continuously improve the quality of their training efforts?
7. Do you have other comments or recommendations regarding NIGMS-sponsored training?
My plan: Use my blog to write some thoughtful answers over the next few days, and then submit my input to their website. Anybody else want to play?
Wednesday, March 3, 2010
Politics
In case I haven't mentioned it previously, I'm from the Southern United States. In my experience, a white person in/from the Southern US is almost guaranteed to be politically conservative. Very conservative. And for my family, my Southern friends, and my family's friends, this guarantee rings very true, meaning my family and my Southern friends are all very conservative. And everyone they know is also very conservative. So everyone I interact with when I go home is very, very politically conservative. And, they kind of assume I am, too.
In my professional life, I'm an academic (even if I am just a lowly grad student). In my experience, academics are almost guaranteed to be politically liberal. Even the academics I knew in the South were politically liberal, so there you go. I guess profession trumps location when it comes to political leanings. And, most of my academic associates also assume I'm politically liberal.
What's fun about this collection of quasi-facts? Well, it means I get to (have to) hear very candid views from both ends of the political spectrum. Sure, anyone can turn on the TV or radio and hear candid views from the people on TV (although in my experience, most people only listen to people on the same side as themselves). But I get to hear it from regular people, all of whom are assuming I agree and are therefore not censoring themselves to avoid argument or hurt feelings. The experience is interesting.
It's really interesting, because I can tell that most people don't ever hear both sides this way. I'm so amazed at how the two sides see each other. How my conservative people see liberal people as so out of touch with reality, so trapped in a bubble where everyone is smart and good-willed, and either has so much they can afford to give it away, or has nothing and wants to get as much for doing nothing as other people get for working hard. And there is a perception that liberals don't understand that many of the policies they support would give government control over everything, and that this control is government's main goal. On the other side, the liberal people I know seem to see conservative people as either really stupid and backwards, or so rich and powerful that they will do anything to keep their wealth and power. And both sides see each other as blind followers who just believe what they're told, because really, why else would anyone believe in or support the politics of the "other" side?
Have I gleaned anything useful from my uncommon perspective? I think I have. I've found there are very, very smart people, with very, very good hearts on both sides, who have really thought things through and made a decision about which way to lean. Of course, on both sides there are also plenty of followers who have gone with the surrounding flow. But for those who have thought about it and made a decision, it really breaks down to different philosophies on people, human nature, and motivation. My conservative people have a more pessimistic view, assuming that people are pretty selfish by nature, and need real consequences for their actions in order to be motivated to be productive members of society. Meaning, if you work hard, you get good pay and live the good life. If you don't work hard, you don't get good pay, and maybe you'll be motivated to work a little harder when you get hungry. My liberal people are perhaps more optimistic, and seem to assume that given the right circumstances, everyone will rise to the occasion of being productive members of society.
Obviously this view is oversimplified, but it seems to be how things break down for many policies. Health care: conservatives think people should work hard to get and pay for their own good health care, liberals want a plan to fall back on for people who end up in bad circumstances. Economics: conservatives want minimal intervention so that natural consequences motivate people, assuming that risk will be rewarded; good, hard work will be rewarded; laziness will not be rewarded. Liberals want more intervention to ensure that uncontrolled circumstances don't dominate the course of people's lives, such as trying to institute policies to give women and minorities a fair chance at education and jobs. National defense: conservatives want to carry the big stick, because the fear of that big stick is the motivation for other countries to leave us alone; liberals want our diplomacy and good deeds to influence good will from other countries.
What do I think? I think there are great ideas on both sides. I also think ideas from either side break down in the extreme, because I think most people do need some consequences in order to be motivated, but I also know life hasn't presented a fair opportunity to each of us. So, here's to being an independent, and hoping that multi-party politics can result in good things getting done, rather than preventing anything from getting done.
In my professional life, I'm an academic (even if I am just a lowly grad student). In my experience, academics are almost guaranteed to be politically liberal. Even the academics I knew in the South were politically liberal, so there you go. I guess profession trumps location when it comes to political leanings. And, most of my academic associates also assume I'm politically liberal.
What's fun about this collection of quasi-facts? Well, it means I get to (have to) hear very candid views from both ends of the political spectrum. Sure, anyone can turn on the TV or radio and hear candid views from the people on TV (although in my experience, most people only listen to people on the same side as themselves). But I get to hear it from regular people, all of whom are assuming I agree and are therefore not censoring themselves to avoid argument or hurt feelings. The experience is interesting.
It's really interesting, because I can tell that most people don't ever hear both sides this way. I'm so amazed at how the two sides see each other. How my conservative people see liberal people as so out of touch with reality, so trapped in a bubble where everyone is smart and good-willed, and either has so much they can afford to give it away, or has nothing and wants to get as much for doing nothing as other people get for working hard. And there is a perception that liberals don't understand that many of the policies they support would give government control over everything, and that this control is government's main goal. On the other side, the liberal people I know seem to see conservative people as either really stupid and backwards, or so rich and powerful that they will do anything to keep their wealth and power. And both sides see each other as blind followers who just believe what they're told, because really, why else would anyone believe in or support the politics of the "other" side?
Have I gleaned anything useful from my uncommon perspective? I think I have. I've found there are very, very smart people, with very, very good hearts on both sides, who have really thought things through and made a decision about which way to lean. Of course, on both sides there are also plenty of followers who have gone with the surrounding flow. But for those who have thought about it and made a decision, it really breaks down to different philosophies on people, human nature, and motivation. My conservative people have a more pessimistic view, assuming that people are pretty selfish by nature, and need real consequences for their actions in order to be motivated to be productive members of society. Meaning, if you work hard, you get good pay and live the good life. If you don't work hard, you don't get good pay, and maybe you'll be motivated to work a little harder when you get hungry. My liberal people are perhaps more optimistic, and seem to assume that given the right circumstances, everyone will rise to the occasion of being productive members of society.
Obviously this view is oversimplified, but it seems to be how things break down for many policies. Health care: conservatives think people should work hard to get and pay for their own good health care, liberals want a plan to fall back on for people who end up in bad circumstances. Economics: conservatives want minimal intervention so that natural consequences motivate people, assuming that risk will be rewarded; good, hard work will be rewarded; laziness will not be rewarded. Liberals want more intervention to ensure that uncontrolled circumstances don't dominate the course of people's lives, such as trying to institute policies to give women and minorities a fair chance at education and jobs. National defense: conservatives want to carry the big stick, because the fear of that big stick is the motivation for other countries to leave us alone; liberals want our diplomacy and good deeds to influence good will from other countries.
What do I think? I think there are great ideas on both sides. I also think ideas from either side break down in the extreme, because I think most people do need some consequences in order to be motivated, but I also know life hasn't presented a fair opportunity to each of us. So, here's to being an independent, and hoping that multi-party politics can result in good things getting done, rather than preventing anything from getting done.
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