HuB Lab

Our lab is now set up in Hennessy Hall. Our lab proper is in Hennessy 362 and our testing suites are 4 suites in Hennessy 370A. You can find Hennessy Hall on the Campus map below. I've highlighted Hennessy in the black rectangle. It is at the intersection of Edina Street with Alta Vista Street. 

To get to our lab. From the picture above, enter the double doors to the left of the car. Take the metal stairwell to the third floor. You'll see a sign for the Timothy Gannon Psychology labs on your left and a doorway. Go through the doorway and our lab meeting area is straight in front of you, room 362. The testing suites are just around the corner. From the stairwell, go through the doorway and to your left. At the turn in the hallway go right and you'll find 370A, the entrance to the testing suites as the first door on your left. You can find some pictures of the lab on our website.

Undergraduate Funding

flickr

There was an old Chrome extension that allowed you to share bookmark folders, but it seems to have disappeared. Here is the next best option.

Here's a list of funding for undergraduates that are interesting and helpful.

NSF PUI
NSF REU
NIH AREA R15
T34 Undergraduate Training
APA Research Opportunities and Internships
Undergraduate Awards and Grants
APS Funding
APA Scholarships
Psi Chi
Iowa Future Program
R.J. McElroy
Monticello College Foundation

Help for finding Post-Docs

Image Processing Lab

There was an old Chrome extension that allowed you to share bookmark folders, but it seems to have disappeared. Here is the next best option.

This is a list of websites to help you find post-docs and post-doc funding. It will likely fall out of date quickly as I likely won't keep looking into post-docs.

General Help
National Postdoc Association
Entering Job Market
PhD Ladder
Small Pond Science - Targeted towards the move to liberal arts
NIH Loan Repayment - Apply for loan repayment while working as a post-doc
Escaping the Ivory Tower - I guess this isn't a helpful resource for pursing a post-doc

Search for jobs/positions
APA Post-Doc Exchange
NIH Project Reporter - search for T32s granted in last 2 years
NINDS T32 Fellowships - Other sections grant T32s great place to start

Programs/Fellowships
Ford Fellowship
Penn-Port
Penn Biomedical
Duke Center for Decision Science
OHSU Psychology Residency
IRACDA General
UCSF-IRACDA
UCSD-IRACDA
Emory-IRACDA
Stanford-IRACDA
NC-State Faculty Diversity
Consortium for Faculty Diversity
Berkeley Diversity Fellowship
NINDS Diversity

Issues in Science

The Magazine First Things recently published an article on the problems of science by Silicon Valley programmer William A Wilson. I'm writing here not to critique his points, as he raises a number of issues that students in my Embodied Cognition seminar have raised throughout the semester (I'll include some of their comments at the bottom of the post), but rather to do what science does and extend his analysis and tie it in to existing literature and commentaries.


In the article, Wilson makes the following points (summarized and bulletized below - my own comments italicized):

1. Science has a replication problem (citing the OSC attempt to replicate 100 psychology studies - though see a critique here and the backlash here for one example) - Here's a suggestion for how to fix this issue - however, a caution on how we try approach replications here and here
2. Positive Result Publication Bias - The "hardness" of a science decreases the reporting of positive results - commentary on that paper here
3. Journals - Impact Factor and Bias
4. Experimenter bias/fraud 
1. "Experimenter effect"- when an experimenter expects a certain result, they are more likely to find it - Here's a suggestion on how to fix that here as well as another suggestion here
2. Publishing the experiments that would likely be accepted for publication. I think he then cites this article from Psychological Science about questionable research practices, but I can't tell for sure since he includes no links or citations
3. Data analysis as an art - P-hacking, HARKING
5. Self-Correcting Nature of Science is nonexistent
1. Scientific Dogma - ignores or outright cover up results that don't agree with accepted dogma - Maybe this example from PLoS earlier this year is an example - where authors credit the hand as being created by intelligent design only to have it retracted because of scientists critiquing the rationale and conclusions
2. Peer-review doesn't do its job - You can find critiques of the peer review process here and here or from this blog here
6. Institution of Science is Old and Resistant to Change
1. Those in power don't want to change (I'll call this the Pyramid Scheme Critique)
2. Systematic Inequalities are present
7. Cult of Science
1. Human bias and error cannot achieve science's goals
1. Here's a commentary on addressing biases
2. "Scientism" - science as a "holy" or "true" discipline
3. Cult leaders who aren't researchers of note or promise proselytize a faulty and disingenuous "truth"

Wilson has very nicely and succinctly summarized a lot of issues that myself along with other scientists have been thinking about for a number of years. If I was able to summarize his points into one, it would be that while science is one path to find "truth" we have to understand that the biases of the people pursing science and the current limitations of both understanding and measurement means that we might not always be right. A little over 6 months before this article was published there was an interesting piece in the NYT and a follow-up on NPR about the role of science in the truth. I want to include a longish quote from George Johnson in his NYT article here:

Science, through this lens, doesn’t discover knowledge, it “manufactures” it, along with other marketable goods.
Altruism and compassion toward the feelings of others represent the best of human impulses. And it is good to continually challenge rigid categories and entrenched beliefs. But that comes at a sacrifice when the subjective is elevated over the assumption that lurking out there is some kind of real world.
The widening gyre of beliefs is accelerated by the otherwise liberating Internet. At the same time it expands the reach of every mind, it channels debate into clashing memes, often no longer than 140 characters, that force people to extremes and trap them in self-reinforcing bubbles of thought.
In the end, you’re left to wonder whether you are trapped in a bubble, too, a pawn and a promoter of a “hegemonic paradigm” called science, seduced by your own delusions.

Marcelo Gleisser in his response for NPR also had a nice quote:

Creationism, the anti-vaccine movement, resistance to genetically modified crops, cellphone radio waves, fluoridation, the ongoing global climate change debate, the risk of certain high energy physics experiments (see my post from last week), all point to a curious "personalization" of science. It's as if scientific issues are simply matters of opinion — and not the product of a very thorough process of consensus-building among technically trained people.

Getting back to the issue of truth Gleisser notes:

Granted, "truth" is a loaded word. What do scientists mean when they say science finds the truth, anyway? One needs to be very careful here, for the very nature of the scientific enterprise implies that truths can shift as knowledge progresses.

A website I love to use to introduce people to the practice of science is Understanding Science: How Science Really Works from UC-Berkley. In their article about science and truth, they note that science tries to build knowledge about the natural world, there are a number of other "truths" to which science can't speak including faith/spiritual beliefs, cultural truths and truths that may be subjective or relative.  So to fall into Wilson's noted "science is self-correcting trap" that fact that we've identified the problems that Wilson notes and the reason that we have a number of experts and non-experts identifying ways to address these issues is the scientific process at work. I don't think there's a group that froths at the mouth more trying to disprove something from their own ranks than scientists. So with groups like the OSC, Open Access/Open Data and improvements to scientific methodology practices and statistical analysis methodology science continues to progress.
---

An addendum: I'm interested to see that this article hasn't been taken up by scientists. It could be that all of the links I've included demonstrate that scientists are well aware of these issues and already harping on one another. It could also be that scientists don't want to take on a religious magazine in the First Things (especially when the article discusses publication bias and human bias in science, but is written in a religious journal and makes the point that we can't trust people because of the agendas they have. Perhaps framed from this religious standpoint, scientists write off the critique as a religion vs science critique and maybe would have taken up this article written as is, but published in a secular outlet).

While I've not seen the article tweeted or blogged about by scientists, I do see it blogged about by religious people and organizations including Intelligent Design supporters. The end the article with this:

If he were active in any other area of science, he could not possibly have gotten away with writing as frankly as this.

Here are some student's thoughts on Issues in Science, saying and thinking the same things:

We had read these 3 papers for one of the last classes on Embodied Cognition

Cesario, J. (2014). Priming, replication and the hardest science. Perspectives on Psychological Science, 9, 40-48.

Everett, J.A.C., & Earp, B.D. (2015). A tragedy of the (academic) commons: Interpreting the replication crisis in psychology as a social dilemma for early-career researchers. Frontiers in Psychology.

Ioannidis, J.P.A. (2005). Why most published findings are false. PLoS Medicine, 2(8), e124.

Cesario's paper addresses many issues that have come up in our class discussions, and I appreciate his explanations for why we see unsatisfying contradictory results in research so frequently. Previously we have brought up concerns regarding the reliability of an effect which has only been replicated by the lab that found the original results. Cesario gives a structure to the replication process which makes this practice necessary, rather than questionable. I agree that it is important for the original researchers to show that they can replicate an effect before anyone else attempts to. Further, I think that by reconstructing each feature of the original study, they will be given more opportunity to consider whether there are elements of the study design contributing to the findings in a way that was not planned for or measured.
He also provides a different perspective on the idea of replicability in multiple contexts, which is a metric we have used to assess the strength of a given effect. We have discussed the influences that situational elements can have on a person's thoughts and behaviors, and sometimes change our expectations for the outcome of a study as a function of cultural context and geographic location. Yet, we do tend to conceive of effects that can be replicated by labs in different countries as somehow stronger. Are effects more important if they can be held universally?
I found the Cesario article very interesting because it proposed a clear framework through which to examine replications in psychology. The proposal that labs should be tasked with replicating their results multiple times before other labs attempt replications seems like a fantastic way to ensure that there is a solid initial foundation for the presence of an effect. However, this proposal runs into the same “tragedy of the commons” problem identified by Everett and Earp. Replicating studies is simply not in the best interests of the initial researchers because they are putting the validity of their scientific contributions at risk and using precious resources and time that could be used to advance their careers and reputation. Thus, the only way for a proposal like Cesario’s to work, a prestigious journal would have to enforce that all submitted articles provide direct replications.

Perhaps even more importantly, I think that psychology researchers should do more to exhaustively record data in a standardized way. In an age where huge swathes of data can be stored online extremely easily, scientists should work to store data on temperature, dates, and even pictures of the lab environment and materials used. I also think it would be useful to have a standardized questionnaire that records basic facts about every participant (age, race, education etc). This data should be formatted in a standardized format in order to make it easy for a computer to search for patterns across studies. Cesario claims that failed replications are often the result of changes in minute variables. Thus, the only way to determine what these variables and patterns are is to meticulously record as many aspects of the study as possible. It’s only then that replications can stop being ambiguous and contribute to our understanding of complex effects.

I found both Ioannidis’ and Cesario’s papers very interesting, specifically because they seem to contradict one another. Ioannidis understands that a “pure gold standard” is essentially unattainable, yet suggests some approaches to improve replication studies and post-study probability. Ioannidis believes in the tightening up theory, method, and execution in order to obtain replication results that can give us a better reading on whether a theory holds water or not. Cesario, on the other hand, seems to place less emphasis on the results of replication studies (for the topic of priming at least) because, among other things, individuals may vary greatly in how they perceive, behave, and react to stimuli. I admit that I was quite skeptical of Cesario’s paper at first, especially when I read the abstract. But when I read the rest of the paper, I found that he explained this point convincingly. It’s almost a shame that he makes a good point, since I feel like his argument places the field of psychology in this nebulous, grey area where it doesn’t fit with true sciences and the scientific method.
This is why I’m glad I read Everett and Earp’s paper last. I like the authors’ idea to make direct replications a requirement for a PhD. It sounds like a practical endeavor that would greatly benefit the field of Psychology. Despite Psychology’s flaws, I’m glad there are still sharp minds and good ideas that could greatly improve the community and research.

With respect to replication studies, we have discussed multiple studies that have not necessarily "replicated" an experiment in it's original form; unless the replication was completely true to the original study, there is always some change that, while claimed not to have significant effects on the results, may have influenced subtle variability in the results. In addition, there have been multiple studies in which experimenters worked in milli-seconds; hence the statistical significance of the data is highly dependent on extremely precise and tight responses and measurement. This type of data collection is suspect to begin with, since, unless the study is done perfectly, subtle errors can occur that obscure the results. However, they are necessary to perform since so much of embodied cognition looks at the influences of priming and metaphor.

On another note, while the theoretical basis for many of the studies we've discussed make sense, there is still a chance that the authors slightly manipulated the data to get larger effect sizes and statistical significance. However, the difficulty in determining the validity of the results for both the original studies and replications can be difficult depending on the experiment. In addition, there are other small factors, like experimenter bias, internal validity and whether or not the participants know what the experimenters were studying, that can influence the results.
Though this sounds dramatic, the corrupt nature of psychological academia represents a larger issue; psychologists motivations aren't necessarily to find new truths about human cognition and behavior, but to publish multiple papers, gain recognition and make money to essentially stay alive. While this pollutes psychological academia with false information, there may be a positive that comes out of the potentially false data: it makes psychology sexy to the general public. By making the results more attractive, psychologists are gradually increasing the amount of potential funding they can receive to perform more accurate experiments. This can increase financial security among psychologists and motivate them to publish completely correct and valid data. On the contrary, psychologists can fall into a hole of continuously producing false data in order to maintain a constant stream of funding. Which ever occurs to a psychologist is ultimately up to them and how much they want to truly add to the field of psychology.

I like the idea from the Everett & Earp (2015) article of requiring graduate students to run a replication study in their field in order to receive a PhD in psychology. I think that having graduate students do this is a much better idea than having undergraduate students run replication studies, and cleans up a lot of the problems with the original idea from Frank and Saxe (2012). If all graduate students were required to run replication studies, the amount of information about the effects found for various theories would increase exponentially. I think that one negative possibility is that there would just be a lot of mixed results created, as we have seen from arguments among different replication studies and original authors. Though I think that the more information and more study attempts the better, I don't know what psychologists would make of it if tons of replication attempts just showed conflicting results. If all graduate students around the country every year created more and more replication attempts, would this be an overload of information? How would we keep track of all of these results? How would we determine which replications are good replications and which aren't? I think that it is a really promising idea, but would like to talk the concept through with the authors to get more information.
In terms of the other two articles, I thought that they worked interestingly in conjunction with one another. Cesario's idea that expectations about replications are inappropriate for priming studies seems to somewhat conflict with Ioannidis's view that most published research findings are actually false. Cesario's article seems to call for less scrutiny of published results, while Ioannidis's article asks for much more of it. I see the validity in both points- though there seems to be a possibility of falseness in many psychology research findings, maybe that is due to undetectable confounding variables from a variety of sources. I think that what needs to happen is more exploration of why a replication attempt fails if it does, in order to find possible mediating factors or specification for which contexts a certain theory applies to.

The readings for today’s class were some of my favorite so far in the course. Something I’ve been struggling with in Embodied Cognition is which effects are real and which effects exist because of a Type I error or some other bias? These readings described the issues in psychological science, disagreement with issues in the field, and potential solutions very well. Asking all Ph.D. candidates to perform replication studies in order to graduate as suggested by Everett and Earp (2015) is a great way to increase the verifiability of psychological science. Though psychology graduate students want and need to conduct their own original research, they still benefit from performing exercises that help them learn new skills. Replicating existing research teaches the psychology researchers of tomorrow these important new skills while improving the psychology research of today.

In his article about priming effects and their replications, I think Joseph Cesario made some good arguments. For example, Cesario’s (2013) belief and suggestion that initial replication attempts should be performed by the author’s of the original study where an effect was found makes total sense. People are very fickle and this means that most psychological effects (including priming effects) are likely to be fickle and subject to slight environmental or contextual changes as well. To avoid the effects of environmental or contextual changes to the experiment, a study’s original authors should perform the first several replication attempts of their findings. Then, if the original authors replicate their original results, other researchers should attempt direct replications of the study to see if effects carry over to new populations and areas. Another argument from Cesario (2013) that I agree with is the fact that conceptual replications don’t help create social verification for psychological research. All conceptual replications do is create additional studies that need to be directly replicated as the experimental effects of priming studies seem to be so sensitive. That said, I disagree with Cesario’s (2013) belief that priming effects cannot or should not have invariance. While I bet most priming effects are not invariant and cannot be seen in most or all people, I think for priming to be taken seriously in the psychological research community there needs to be some effects that are close to being universal.
We have been struggling with the issue of failed (and occasionally successful) replication studies throughout the semester. It has always been a struggle between the original study saying they have found something interesting and another study coming up with null findings. However, throughout this, we generally saw it as a question of who is right? The original experiment or the replication? And after reading Cesario's piece on priming, I believe we have been asking the wrong question. Both studies could be correct, or they both could be wrong. Even changing the site of a study can effect the results of the experiment, even if the methodology stays the same. We have touched upon this idea some when we consider the cultural differences between participants groups, but I don't feel that we have ever allowed the conclusion to be that maybe both studies are right. But the question then becomes, if both studies are correct, which one is useful?
This question of what is useful and what is not gets at many critics strongest point, if both can be correct, then what does that really tell us about the human mind? How does it add to the field? At this point, I would agree with Cesario when he says it doesn't mean much. Without having the experiments replicated by the same labs, it is impossible to tell whether or not an experiment demonstrates an effect for that population. Without a base of some very specific examples of experiments that are replicable, even within the same lab, then it will be difficult for theories of social priming to gain any traction. Einstein is quoted as saying, "Insanity is doing the same thing over and over again and expecting different results." By this definition, psychology could be helped by introducing some insanity to the scientific process.

Hitchhiker's cliff notes to a career in neuroscience 2

I realize in many of my posts I seem to lash out at something. Often its a piece of news from the realm of higher education, but recently it was the seemingly glib treatment that researchers laid out a career guide in neuroscience. They began by glossing over the oversupply of trainees and the intense level of competition both within academia and in the careers that neuroscience trained scientists could easily transition to outside of academia. They then went on to say that there are four things you need to succeed in attaining your own neuroscience research lab within academia that I summarize as, mobility- you have to go where the jobs are, networking - you need plenty of connections to succeed through the backchannels and other paths outside the traditional structures, build your CV - you need to publish a lot in high impact journals in order to chase your own independent funding, and finally engage in neuroscience and the next generation - you have to like what you do and help others like it too.

In my previous post I gave my impression of what a career guide to becoming a research professor actually looks like. Here I'll give another impression expanding the guide to wanting to work in academia more broadly.

1. Engage in neuroscience and the next generation
2. Taking your time
3. Train broadly (yet also specifically)
4. Networking and saying yes (and no strategically)
5. Reflecting and Introspecting

1. Engage in neuroscience and the public/next generation
Before starting down the path towards a career in neuroscience you really have to love the topic and the process. The reason that people with perfect GPAs and GREs but no research experience don't get into graduate school is because without evidence of having gone through the research experience and wanting more, its a gamble whether this intelligent person has the qualities that make them a good scientist. Much of the research process is a grind and filled with ambiguity and failure. You have to enjoy both being by yourself and at times with a lot of other people. You have to enjoy gray areas and trying to sort through tons of conflicting information. You have to go through the grind for few rewards, internal or external. Graduate school is hard and probably becomes nearly impossible if you don't enjoy the topic that you're studying.

Sometimes when you're down in your silo working away you can forget about the outside world. In order to have a future for you to be able to keep doing your work, its necessary to share you process with the public and school-aged children so that they can be excited and understanding of what you're doing. Without public support there will be no academia and no support for research.

2. Taking your time
In the second half of college as students start to think about what they want to do in the future, sometimes I hear students say that they're just going to go to graduate school because they're not sure what they want to do. It scares me to hear that because it seems like they're skipping step 1 above. While I realize that the road to your first position as a tenure-track is a long one (2 years masters, 4 years PhD, 2 years post-doc), it seems that most people who are in the position of giving grants and hiring professors see trainees as fine wines or spirits that need years of aging before they're ready. That means that in general many successful people put in time as a research assistant/lab manager after college and maybe pursue a tangentially related masters and maybe complete multiple multi-year post-docs. Also, within each stage the general theme seems to be hurry up and wait, where you rush to do something but then you have to wait for someone or something. Most deadlines are not even set in stone, so by taking your time to do things well, one time you can save yourself time.

3. Train broadly (yet also specifically)
The triumvirate of academic assessment includes research, teaching and service. If we visualize that triumvirate as a pyramid in terms of the expectations, the bottom of the pyramid is research with teaching in the middle and service at the peak. No matter the path you want to take in neuroscience either inside or outside academia, the foundation of your training is in research. Even if you're looking to train towards becoming a teaching focused professor or a non-profit worker, your increase in effort or experience in teaching or service cannot come at a cost to your research. Graduate schools are now recognizing that there are not enough academic positions available for all of the graduate students who are there (either as cheap researchers or cheap teachers) and have begun to provide training opportunities outside research. As much as a PhD is a ticket towards a research, teaching or service oriented career, the specific skills that you gain as a researcher set you up for success in all of the other realms.

4. Networking and saying yes (and no strategically)
Meeting people both formally and informally in academia is one of the most important aspects of success. The more people you know the better your chance to find out about opportunities that are either not advertised or only offered to select people. Knowing people can help you find jobs, publish in special issues or edited books, speak at conferences and be invited to contribute to grants or new companies. In order to meet people, you have to be open to experiences and be willing to say yes to almost every opportunity. Early in your career its important to say yes to basically every opportunity while keeping in mind that not all of them will work out. After establishing yourself, then you can start to say no strategically while at the same time reaching out to others to make connections.

5. Reflecting and Introspecting
The path to a career in academia is a long one with a number of built in check points. A number of people fall victim to the sunk cost fallacy and stick with the career long after they should. There are both formal and informal requirements depending on your career path and career stage that allow people to check-in and see where they compare. Its difficult if not near impossible to give up on something after putting 20 years into it. Its also especially frustrating when you feel that things outside your own power and effort are the reasons that your (in)formal requirements don't meet up. The path is long and life and career circumstances can change quite quickly, but by following the first four pieces of advice you shouldn't have much difficulty pivoting your career focus at any stage.

The Hitchhiker's cliff notes to a neuroscience career

Source

Both my wife and I are on a galaxy wide trek in attempt to find our path in the neuroscience academic field. While unfortunately our treks have taken us to different zip codes for another year, Neuron published a guide in a recent NeuroView to help us make sure that we're on the correct path. Interestingly, since "throngs" of scientists and aspiring scientists enter the field each year with no less that 1.7 million individual scientists worldwide actively publishing on the brain and behavior since 1996, as the authors state, "not all of these young researchers can make an academic career in neuroscience."

The authors discuss instruments and initiatives that they feel can help people (with a focus on European researchers) progress through early- and mid-career steps:

1. Mobility
2. Networking
3. Build a CV and Seek Advice
4. Enjoy Neuroscience and Engage the Next Generation

The authors are describing a career trajectory towards running your own research lab at a research university, which is important to keep in mind as I revise their suggestions:

1. Publish early, publish often, publish in "glamour" journal
2. Repeat

If you want a research career in neuroscience you need to start publishing in undergraduate with at least a first author publication from your senior thesis. You then likely need to get a "glamour" first author publication in your masters or first year of PhD so that in your second year you can obtain fellowship funding (e.g. NSF, NIH, CIHR/NSERC) from a national funding source. Then through the rest of your PhD you need to publish first author "glamour" articles and use your "networking" and "mobility" and collaboration to beef up your CV with co-authorships in specialized and field-specific journals. With over 10 publications in your PhD you can then find a post-doc and maybe even bring independent post-doctoral funding with you where ever you go (remember mobility means you get to go where ever). More "glamour" first author pubs and at least 20 author publications before you're ready to go on the market, you better make sure that you were PI or co-PI on a medium or large grant before attempting to apply for jobs.

I think any good travel guide not only includes the things you should do, but also the things that you should avoid, the "tourist traps" if you well. So I''d like to hear or see the things that young scientists should not do if they want to find a career in academia. I'd also like to see a guide that goes beyond the research lab PI role to encompass other paths in academia.

Continued Misunderstanding of the Function of Higher Education

In my free time my favorite thing to do run. I think I was drawn to research for many of the same reasons that I love running. You need to be somewhat crazy, you have to put in long hours of work for only small personal victories, only people who do the same thing as you, in order to excel you have to good at a number of seeming unrelated activities, and finally at the professional ranks you have to answer to people who have little understanding of the inner workings. Earlier this week I went to the Boston Marathon to watch my wife run (a PR in 3:17:23). As a spectator of the marathon, even though I was only watching people run 26.2 miles in 2 to 5 hours, I was actually watching the culmination of hours, months and even years of hard work and preparation. At the professional level, the men and women race winners were each awarded $100,000 for 2 hours of effort and similar to other professional sports, many mistakenly believe that they are only compensated for their time in the limelight. In run training, you have to combine hours of volume training, hours of race pace training, hours of speed work, hours of strength and form training as well as cross training, active recovery, proper diet and sleep. So instead of $50,000 an hour, if we only count the days elapsed so far this year, the athletes likely only made $76 an hour.

In my other field, in the past week, two examples of people with little understanding of higher education made a similar mistake in only paying attention to the limelight and forgetting everything else behind the scenes. In Iowa, a legislator introduced a bill that would have the professor with the lowest ratings in teaching fired while in North Carolina an education bill would mandate 4-4 teaching for all faculty. While the bill in Iowa died in committee the idea behind it shows almost no understanding of the role of faculty. Just as the two hours on the marathon course are just a sliver of what makes a marathoner, the three hours per week in one particular course are just a sliver of what makes a professor a professor. I value the importance teaching and have worked hard to gather feedback from my students throughout my career teaching but I am sympathetic to professors who struggle in the classroom. However while student evaluations are one of the only ways that teaching ability is assessed, this article discusses some issues with student evaluations and suggests that they may not be the best way (check out the comments as well).

In North Carolina, Senate Bill 593—“Improve Professor Quality/UNC System” would “ensure that students attending UNC system schools actually have professors, rather than student assistants, teaching their classes.” The bill asks professors at the research institutions of North Carolina to teach 4 courses a semester and ignores the fact that if tenured faculty are not teaching courses, its likely adjunct professors. Again while 12 hours in the classroom per week may not seem like much, its just the tip of the iceberg with lecture preparation, grading, and meeting with students. But this focus on teaching at Research I institutions ignores the fact that professors at these institutions are supposed to be creating knowledge in order to pass on that knowledge in the classroom. In my six years at research focused universities (Iowa, York and Toronto) I have met very few professors that were openly hostile towards teaching with most enjoying teaching (in the broader sense, including time outside the classroom). However, almost all of the professors that I know teaching 1-2 courses a semester have almost no time as it is. Few take time off, few sleep regular hours and few have hobbies outside teaching. Asking them to teach 4 courses but place the majority of their evaluation on their research will lead to research professors in North Carolina to leave in droves with no one looking to take their place (despite the huge oversupply of candidates).

If anything I think these two bills suggest that higher education needs to do a better job of communicating its role in society. College is not just a place for job training, so in order to avoid further commodification of higher education we need to not only communicate the importance of our research, but our teaching and engagement.

Edit: 4/27/15 One day after I write this, this article is published on the future of the American Research University. This passage echo's my sentiments above:

"Those of us leading or working in research universities, especially public ones, face the urgent imperative to articulate and give full-throated explanations of the extent to which university research not only brings economic and social betterment (through new medicines, policies, products, jobs, etc.) but also is crucial to the educational mission. It drives discoveries that can be commercialized to enrich innovators and their backers, and it ensures that those innovations will be deployed to sustain the vitality of our economy, our society, and our human values. Research is also a good in itself across the full set of disciplines and fields that constitute university life; it is an aptitude and skill that students, both undergraduate and graduate, learn in college that can be of lifelong value; and it is a force that generates new knowledge — and new modes of teaching and learning."

SfN Hill Day

Yesterday was SfN Hill Day, an annual event in which neuroscientists advocate for the importance of biomedical research and funding. From the SfN website, they note that the purpose of the event is to

"Meet with their congressional representatives to discuss advances in the field of neuroscience, share the economic and public health benefits of investment in biomedical research, and make the case for strong national investment in scientific research through NIH and NSF."

I searched through the hashtag, #SfNHillDay and recorded the Senators and Representatives (or staffers) that were tagged as having met scientists. In total, 18 Senators and 24 Representatives met with scientists to discuss the importance of funding and investment in neuroscience research. I found the timing of the Hill Day interesting as Rick Domann, a Professor from the University of Iowa has recently tweeted a few interesting articles about science funding in the US including one from Science Magazine where 1000 senior investigators dropped out last year and one from Research Trends about the NIH. Together these two articles suggest problems in biomedical funding. While I am all for more money being responsibly invested in biomedical research, in particular neuroscience, we should first consider fixing a broken system.

Going forward, it will be interesting to watch how these 42 congress people vote and advocate for science funding. As the 2015 NIH budget looks relatively flat, I wonder what the future of funding will look like. Will public funding levels continue to decrease and will we see a rise in crowdfunding of science? As scientists look towards this bureaucratic bypass I wonder what types of institutional oversight and quality control measures will be put forth in order to make sure that the best studies are being put forward for the opportunity of crowdfunding.

"Lack of critical thinking in strike"

In college I avoided English classes like the plague. After my first year writing course, I only took one English course and it took place during Interim with the topic covering protest in American literature, comparing and contrasting literary authors and American singer-song writers (i.e. I listened to Bob Dylan and Bruce Springsteen and analyzed how their lyrics spoke to themes found in Steinbeck and Ellison). When approaching a critical analysis of any piece or idea you can generally take one of two tracts, a surface level and a deep level. Although not always true, the track you take is often dependent on your experience with the piece or idea. In a recent article in The Star on the strikes occurring at York University and University of Toronto, the author comments on a lack of critical thinking, but appears to come at the issue so far removed from it, that in their analysis citing a lack of critical thinking, they miss all of the deeper issues that with critical analysis would be revealed.

I've never heard of the author of this article before, Martin Regg Cohn, but he is a political commentator for the Toronto Star. Wading through the article, its hard to find his point. Under the title is a subtitle: "Labour strife has exposed fault lines in university faculties — byzantine hierarchies where part-time teachers toil in classroom sweatshops." while a caption for the included photograph says: "While a hardy band of low-paid contract lecturers bear the brunt of teaching, a coddled elite of tenured professors are among the best-paid on the planet — while teaching fewer courses than ever, and sloughing off research duties." and the article concludes: "But as other sectors adjust to upheaval — from manufacturing to media to hospitals — we should demand greater accountability and clarity from universities. It’s not just students who deserve a better deal, but part-time teachers, too. Listen to the canaries in the ivory tower." What I pull from these comments is that Mr. Cohen believes that Universities have created two classes of workers with tenure-track faculty riding high hogs with no teaching responsibilities and zero cares about research output while contract faculty perform all of the teaching. He cites a "hallowed" rule that tenure-track faculty divvy their responsibilities 40-40-20 among research, teaching and service, that some professors hadn't published or received funding in 3 years and were well compensated. Taken together I understand this piece as a diatribe against tenure-track professors, however, as the title suggests, Mr. Cohn lacks critical insight into the issues underlying the environment from which these strikes are arising.

At the risk of sounding like a broken record, I've written about these issues before (here and here) with the gist suggesting that we need to re-think how we evaluate and reward research output and reconsider or come to an agreement on the roles of universities/colleges, in particular research universities in society. Without the private sector respecting a PhD for the general skills it provides (similar to the general skills that a liberal arts education provides), there will continue to be a glut of PhDs who are hoping to work towards a tenure-track position, with few other options. As long as there is pressure to enroll as many PhD students as possible in order to produce as much as possible, we'll be unable to escape the cycle of enrolling more students and turning out too many PhDs. Mr. Cohn and others deride faculty for their apparent unwillingness to teach, but faculty at R1 institutions receive little to no reward for teaching (in the narrow sense of teaching in classroom). Even outside of Universities, few people talk about the best teaching institutions unless they're high school guidance councilors. Most of the time that colleges are mentioned for their prestige or impact, the reference is to their research output not how many classes their professor taught that semester or how high their ratemyprofessor.com ratings are.

We can look at these strikes on the surface and make very little contribution with our comments, tenure track professors don't teach enough, tenure track professor only work 9 months a year and are paid too much, TAs, contract faculty are only working part-time, why are they expecting full-time wages. Or we can look past these surface issues and try to understand why colleges and universities value research output from their tenure faculty, why they rely on cheap options to teach every expanding classes and why little will change without massive overhaul across the private sector, government funding and the research culture.

International Women's Day

Yesterday was International Women's Day and like most of society, I'm late to recognizing women. IWD is meant to empower women and raise awareness about the prejudice and hardships that women implicitly face based on their sex. In science and academia women face a number of issues that are slowly and hopefully successfully being addressed.

My wife and I have a unique perspective on these issues as we have the same educational background albeit slightly different research agendas. When I finished my PhD and went to take a postdoc, there was implicit belief that she would move with me and finish her final year of her PhD from afar. When we said that she wouldn't do that the next question was whether she was looking for postdocs or jobs in Toronto for when she finished. Finding a job in academia is hard, finding jobs for academic couples near each other is very difficult and finding jobs for academic couples in the same field is likely impossible. With these issues if we look into these couples and their difficulties we likely see that for women have the more difficult job search in the couple.

In the midst of the difficulties applying for jobs I recognize that as hard as it is for me, my wife faces a number of biases both within and outside of academia. All of her thoughts and actions carry certain connotations that are generally viewed negatively. It also seems like she has to work twice as hard to get half as much back. With a full competitive fellowship, multiple first author publications (with a clear research plan that can be carried out with undergrads) and experience teaching at two different small liberal arts colleges, she seems like the perfect candidate for a tenure track position at a liberal arts college, or as visiting professor or as a teaching postdoc. I don't think about it too much but I wonder if I had been a female if my experience through grad school would have been different, would have applying for postdocs been different and would apply for tenure track jobs be different.

In my own supervision of research and some of my engagement work I have worked to advocate for women in science. I'll continue to fight for the rights and treatment of women in science and recognize my own implicit biases and advantages as a male scientist, while doing my best to not discount that differences in sex are leading to two very different experiences in science.

Roman Research Institute 25th Anniversary Conference

The conference began a little slowly on Monday morning so I guess it wasn't just the attendees with a case of the Mondays. Sitting in one of the meeting rooms I was surrounded by hundreds of professors, clinicians, postdocs and graduate students and although the print was tiny and it was difficult to read, I found few if any community groups or members represented amongst the crowd. As the introductory speaker began I couldn't help but wonder what the cause of the lack of community members was. Was there a lack of interest from the public, was the registration fee too exhorbinate, or are conferences one of the last bastions of the ivory tower where we academics can hob nob with each other, speaking in our jargon and buzzwords without the care or need to translate our speech. As I look to the next three days of the conference I'll think about the role of conferences in academia, in science and in society at large.

Conferences were originally a way to exchange thoughts and ideas and bring academics together to debate and collaborate. In the 21st century, conferences feel like an outdated and outmoded function. Communication across the globe happens continously and instantly, waiting to get together on a specific day in a particular place doesn't fit with our capabilities today. However, that might be symptomatic of what I suspect conferences are actually for, the amorphous term, networking. Gathering people in fun or exotic locations with the excuse of a meeting allows big players in science to get together and meet outside of the conference itself. It allows them to introduce their trainees to their colleagues and protect their inner circle. Trainees at each level are either in the game and trying to figure out a way through networking to claw their way to the next notch on the totem pole to tenure or out of the game and trying to have fun at the bars or local attractions.

Since networking is likely why conferences still exist in their antiquated form and the exchange of ideas is just a consequence, I can understand why community members are not present. As science begins to turn to the public directly for funding (i.e, crowdfunding), perhaps science needs to reconsider how much they value how conferences are run in their current form. Taking money from the people and not working to make conferences accessible will lead to the public abandoning science and leaving scientists stuck like Rapunzel in their ivory towers. Even though I'm guilty of the problem of one way communication with this blog, my twitter and if i start my podcast, we have to figure out how to communicate with and listen to the public as we look to the future of science.

Reviewer Etiquette: Just because you're anonymous doesn't mean you need to troll

scienceblogs.com

Peer-review may be the cornerstone of the scientific process as it is the gate through which both forms of scientific currency (publications and grants) must pass. Peer-review serves as the quality control system in which all scientific discoveries and ideas are scrutinized and and vetted by other experts. Peer-review is meant to make scientific communication trusted, but peer-reviewed work isn't necessarily correct or conclusive, even if it has met some standard of science. After the peer-review process is over and a paper/grant has passed through the gate, it doesn't mean that the process is over, science must deal with it somehow either through responding with commentary, other related studies or replication attempts. However, it often seems as though peer-review is treated as the final say, that flaws are magnified and if the paper doesn't meet some arbitrary standard or give the anonymous reviewer enough citations then it is the end and that idea or that study is stopped dead in its tracks right then and there.

In general the responsibilities of reviewers are to:

• Comment on the validity of the science, identifying scientific errors and evaluating the design and methodology used
• Judge the significance by evaluating the importance of the findings and how/where the findings fit in the literature (including identify missing or inaccurate references)
• Determine the originality of the work based on how much it advances the field
• Recommend that the paper be published or rejected. Editors don't have to heed this recommendation, but most do (this also varies by the number of reviewers rounded up - sometimes the decision needs to be unanimous, sometimes if the reviews are split another is brought in to break the tie and sometimes the editor makes the decision regardless of the reviewers)

In single-blind (where the authors don't know the reviewer identities) and double-blind (where neither reviewers nor authors know each other's identities) post-hoc (as opposed to pre-registration) review tend to have a few problems. 

1) Focusing on methodology when the study has already been completed

Pre-registration would seem to solve some of the most frequent reviewer requests, methodological issues, including adding new conditions, new controls or becoming obsessed with the fact that an experiment was run a particular way that they don't quite like. This change would take care of the first responsibility of reviewers, correcting errors in the design and methodology before the study even takes place. 

2) Lack of responsibility/accountability for reviewers

The removal of reviewers being blinded to the authors and readers may help change the level of constructiveness of the comments made in reviews. A tumblr aggregates some of the reviews that don't appear to fall into any of the responsibilities I mentioned above. Removing the veil of anonymity should help to improve the dialog and impact of the review process (here and here). We may even give more significance and value to reviewing. Review is a service and valuable contribution, but given little value in the eyes of the determination of your impact as a scientist. Often it seems as though review is passed off to trainees whose only experience evaluating the literature comes from lab meetings and reading groups where group think causes everyone to dump on the papers and nitpick the papers into oblivion. By naming reviewers (as the Frontiers family does) we give reviewers acknowledgment and accountability. We could go even further and note what they contributed to the study and figure out ways to evaluate the impact that individuals make as a reviewer similar to how we use authorship on papers to evaluate impact.

In the end, peer-review is not the end of the process but just a part of the process that extends far beyond a paper being published. By giving more responsibility and reward for review we should improve the process and remove the "me against the world" feelings shared by both authors and reviewers.

Is a Strike == a "Labor Situation" == a "Labor Disruption"? Only when they're framed the same

globeandmail.com

I've recently noticed I use a lot of parentheses in writing and I think its a side-effect of years of academic writing. Sometimes I wish I could represent parens in speech outside of talking under my breath. One place I recently noticed a lack of verbal parens where there should have been has been in the discussions of the strikes by CUPE 3903 and CUPE 3902 at York University and University of Toronto. Cheryl Regehr, Provost and Vice President of the University of Toronto, recently wrote in the Huffington Post (with a great response from a UofT graduate TA here) that teaching assistants rejected an offer of raising their hourly wage to $43.97 but forgot to add that with that increase in hourly pay their total hours changing (decreasing from 205 to 180). Without the information in that paren we can only see the TAs/contract faculty as greedy, unappreciative and spoiled brats. When you do the math the TAs suddenly don't look so greedy. Now TAs make $42.05 with a 205 hour cap for $8,620.25 while the proposed package is equal to $7,914.60, otherwise know as a $700 decrease! 

globeandmail.com

Regardless, the point the TAs/contract faculty are making is that UofT could offer $15,000 with a 1 hour cap or $60,000 with a 0.25 hour cap, or $247,355.32 (the pay of Provost Regehr) with a cap of 0.06 hours, but the problem is not the pay per hour. The problem lies in the cap of $15,000 in funding which is less than the poverty line for a single adult in Toronto. But I also suppose this $15,000 funding package is where the real problem lies. A number of people question whether a "part-time" job really deserves to be paid at a "full-time" rate, especially when the TAs are already being paid to go to school.

nationaladjunct.tumblr.com

Last week brought us National Adjunct Walkout Day and was quickly followed by these strikes highlight systemic problems in academia. Its hard to find data for attaining tenure-track positions that encompasses R1 institutions, primarily undergraduate institutions and community colleges, but the figure is likely much lower than how many want to. Although I don't have the exact figures, it seems like the number of students who think they can "go pro" and those who actually do are in line with college athletes' perception of their ability to go pro and those that actually do. Although a PhD should not only be seen as a path to working in academia, it is often the carrot used to attract students and outside academia a PhD is generally not viewed overwhelmingly positively. Broadly, the goals of Universities are to create and disseminate knowledge and that occurs through three avenues, research, teaching and engagement. Previously, I discussed some of the misperceptions of the goals of Universities and I see some of those issues creeping up in the strikes. 

1) We're training too many PhDs

Early booms in research funding drove up the need for labor to complete research grants which spiraled into the need for a large number of cheap trainees to put out ever higher and higher amounts of research in order to compete for more grants in a shrinking pot of money. Or put another way, we've created a system where tenure-track faculty, in order to be competitive for grants and tenure, need large labs of highly motivated trainees because without high output their labs can't progress.

In a similar vein, reduced funding at the federal and state(or provincial) levels increased the need for Universities to find alternate avenues of funding which led to increases in the number of students, in particular foreign students (as well as an increase in their tuition costs). This led to the increased need for more cheap instructors to teach the increased number of students. With the number of tenure track positions holding steady and an ever increasing pool of PhD graduates, with few equivalent positions outside of academia we've created an underclass of highly educated individuals with no where to turn except for part-time teaching work while holding out for a tenure-track position. 

2) What is the role of Universities and Colleges and what are students hoping to get from a college education

In Scott Walker's latest brush with education in Wisconsin we see some of the misperceptions of what college professors do. As I stated earlier the role of higher education is to create and disseminate knowledge. The triumvirate of higher education, research teaching and engagement map onto those rules with research to creation and teaching/engagement to dissemination. Across the scope of higher education we see the emphasis of creation and dissemination skewed to smaller or greater extents towards one role or the other with R1 institutions skewed towards creation and primarily undergraduate and community colleges skewed towards dissemination (with a number of institutions not fitting into this broad generalization). At large research institutions, teaching, defined narrowly as teaching a course, is generally viewed as a secondary responsibility. From the outside, that might be surprising, but when you look at how tenure is assessed (emphasis on research productivity, i.e., papers/grants) and how administration assigns instructors to courses (with over 60% of courses taught be non tenure-track faculty) we see why faculty at large research schools focus on research (which also involves teaching). 

While we recognize the value of a highly educated populace, a number of people question whether college is simply expensive job preparation. We're less than a week into the strikes at UofT and York and if you check the strike related hashtags on twitter (#WeAreUofT, #YorkUStrike, #CUPE3903, #CUPE3902) you find a mix of support from the TAs/CF and others in solidarity with a number of undergraduates either posting that they're mad about the strike and want to go to class or posting about the fun things they are doing in their "time off." Like the misperceptions of what Universities/colleges are for there are misperceptions about what students should be doing in college. If you go to college and simply attend class, take exams, write essays and work a part-time job then yes, college is simply job preparation, but in that case, probably not very good preparation. If on the other hand going to classes seem like a small part of your college experience because you're working, taking internships, participating in extracurriculars (whether its sports, music, drama, or student clubs) and challenging, stressing and growing, then college is both (excellent) job preparation and for creating a highly educated populace. 

In the end, both of these issues come down to how we as a society value higher education. Do we feel that investment in the research of colleges/universities and in the education of our populace as a whole is a worthy investment? If we don't value the research or Universities/colleges or feel that private industry will make up the difference then we should continue defunding higher education. If we think that our populace attaining higher education is not a worthy investment then we should pass the costs of attending both secondary and post-secondary onto only those who choose to attend. However, before we make those decisions we have to get everyone on the same page and understand what higher-education does and why it does it as well as agree what attending secondary and post-secondary schooling actually does for students.

Are Athletes:Sports Journalists as Researchers:Science Journalists?

In the hype leading up to the Superbowl, the biggest story may be Marshawn Lynch's interactions with reporters. This style of interaction appears to be spreading to other sports stars as well and it makes me wonder about the role of sports journalists. In today's social media dominated society sports stars and fans have more direct access to each other than ever before and as with other sectors being revolutionized by technology the middle man is being cut out.

Sports writers used to be the conduit between athletes and fans, but today athletes and fans can connect through any number of avenues from Twitter, to Facebook, to Tumblr, to personal websites or even reddit. Athletes can use any combination of these social media outlets to craft their own narrative and relationship with fans rather than relying on sports writers to dictate their image. This changing relationship between athletes and sports writers appears to be similar to what is happening between researchers and science writers. A number of researcher friends have posted and commented on this recent poll complaining about the disconnect between beliefs/perceptions of the public and scientists. So what is causing this disconnect, does the responsibility of science understanding fall to the general public, the scientists communicating their findings, or science writers translating findings from scientists to the general public? As social media has opened up new avenues of communication for athletes, it also has for researchers. Grant organizations are recognizing the importance of putting in knowledge translation plans in place before projects start. However, without the public being interested in learning about science findings, whether the information comes from science writers or researchers, translating science may just be akin to throwing paper in the wind.

The poll I linked earlier also had a number of interesting questions about the role of science in society. More than half (57%) and a little under half, (43% and 40%) of scientists thought that major problems are that  there is a lack of public interest in science, lack of media interest in science, and too few scientists communicating findings. While the public has a fairly positive view on the impact of science on society, there is a trend towards negative feelings with the public lessening in their perception of U.S. achievement in science, the contribution of science to society and the return on investment in science. So it seems that while science and researchers are attempting to reach out more than ever, the public may not want to hear it. Before science and researchers work on knowledge translation it seems that we need rehabilitate the image and trust in science and researchers.

A recent demonstration of the public's mistrust in research and higher education comes from Wisconsin where Governor Scott Walker has proposed a slashing of $300 million from the UW-system over the next 2 years in order to help balance the budge and offer the institutions more flexibility in their own governance and spending. After announcing the plan and receiving backlash he also suggested that professors teach more classes because they were not doing their jobs on the 2-2 schedule of teaching at large research institutions. This brought noted backlash from professors and others in higher-education who suggest that between research (the most highly valued asset at research institutions) teaching and service, professors spend over 50 hours a week working. However, others are unwilling to "break out the tiny violins" and see professors and researchers as underworked and overpaid. Interestingly, the article links a page that lists UW-system pay and if you look at the first page the top 3 paid employees are coaches and sports administrators while the rest of the page is almost entirely dominated by marketing, economics and law professors making a fraction of what they could make outside higher education (pay for these professors is 2-5 times higher than other disciplines because of the competition/availability of jobs from the private sector). So before we can work on knowledge translation, we need to work on the image of higher education and research so that the public can trust and be interested in research.

Edit: 1/30/2015 - I was looking more into the Wisconsin higher education budget issue and see that it parallels the battle with K-12 teachers in the state just 4 years ago with many of the same claims, that they are overpaid and underworked. It seems that much of the misunderstanding of teachers at K-12 that is magnified at higher education levels is that time spent in the classroom in front of students is the only time that should count as work.

Edit 2: 1/31/2015 - I found this article discussing the same issues and article that I mention here about the divide between the public and science/higher-ed. They offer one possible bridge with open forums for scientists and the public (in particular those who are most against various scientific findings - vaccines, GMOs, etc) to discuss issues.

Edit 3: 1/31/2015 - Great discussion on Science Friday about the Pew findings