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Claude Steele and many other sociologists elaborate on the concept of stereotype threat, which leaks into discourse surrounding the topic of women in science. While this field of research is only recently accumulating more quantitative evidence, the idea of women in science reporting greater inclination to feelings of imposter syndrome and the like is easily related to the discourse of Robert K. Merton on the sociology of science in general over half a century ago:

…when statements are doubted, when they appear so palpably implausible or absurd or biased that one need no longer examine the evidence for or against the statement but only the grounds for it being asserted at all.*  Such alien statements are “explained by” or “imputed to” special interests, unwitting motives, distorted perspectives, social position, and so on. In folk thought, this involves reciprocal attacks on the integrity of opponents; in more systematic thought, it leads to reciprocal ideological analyses. On both levels, it feeds upon and nourishes collective insecurities…

[*Footnote]: Freud has observed to seek out origins rather than to test the validity of statements with seem palpably absurd to us…On the social level, a radical difference of outlook of various social groups leads not only to ad hominem attacks but also to “functionalized explanations.”

–Robert Merton “Paradigm for the Sociology of Knowledge” 1945

Ideally, we do not let our perception of gender interfere, consciously or unconsciously, with our interpretation of the quality of another individual’s work (i.e., ad hominem attacks). Problems include (1) overcoming our initial reaction to categorize individuals in broadly defined stereotypes associated with historical (out-dated) gender roles and (2) appealing to any fallacies supporting the maintenance of out-dated gender roles.

Ask me to describe myself, and I will describe my aesthetics: biology, foreign languages, philosophy, post-modernism, and critical theory. Ask a stranger to describe me, and “female” is a socially acceptable general category.¹ From this category, one may already make many assumptions of who I am and the quality of my work; however, the social category of “woman” is not one with which I would immediately self-identify, though I reside in this category when I check boxes on documents, select a gender pronoun, or use the restroom. Restrooms in the work place are usually segregated into binary divisions of men and women, and there’s a historical (subjectively out-dated) reason for it.

Assimilation of men and women in universities and the work place did not happen overnight. Although social boundaries have expanded, the women’s restrooms in buildings (not recently renovated) still reflect an out-dated gender bias. “Women in Science,” one may define being “in Science” intellectually, occupationally, or even architecturally. A woman in a lab or building where STEM (science, technology, engineering, mathematics) related work takes place, in some regard, is a woman in the realm of science. Restrooms in older STEM buildings were constructed when gender ratios were noticeably different from now, so male restrooms in subjectively antiquated STEM buildings may have 2-3 times more stalls and double the square footage of adjacent female restrooms (I discovered this from stealthy, late-night investigations, when gender-bias in restroom size and organization became apparent to me).

The restrooms (the toilets, los baños) are an unspoken divider between consumption and its precipitating waste product, and this distasteful observation may be the reason why the topic of gender bias in the construction of these “places of human retreat” is generally ignored. Restrooms linger unobtrusively down the hall, whence scientists meander to return to work. Little is spoken about why some scientists go into one door (the one with the stick figure wearing an inverted triangle dress) while some scientists enter the other.

Matthew Kopas writes on the history of gender-segregation starting in the late 19th Century in Massachusetts to protect women in the work place. Unisex bathrooms in dorms provoke outrage in some online college discussion boards as something indecent. This calls into question the binary division between male and female. Humans may self-identify as neither or both genders, or somewhere along a continuum. Are gender-segregated bathrooms reinforcing a hetero-normative work environment? 

Donna Haraway, author of A Cyborg Manifesto: Science, Technology, and Socialist Feminism in the Late Twentieth Century, describes the exclusivity of categorical naming (e.g., “male” and “female”):

“It has become difficult to name one’s feminism by a single adjective — or even to insist in every circumstance upon the noun. Consciousness of exclusion through naming is acute. Identities seem contradictory, partial, and strategic. With the hard-won recognition of their social and historical constitution, gender, race, and class cannot provide the basis for belief in ‘essential’ unity. There is nothing about teeing ‘female’ that naturally binds women. There is not even such a state as ‘being’ female, itself a highly complex category constructed in contested sexual scientific discourses and other social practices…”

In the context of restrooms and women in science, we are confronted with this interesting division that calls to question what it means to be “woman,” which would be, based on this simplistic binary division, to be “not man.” Historically (and in certain extant cultures with which others are far more versed than I), to be a certain gender implies (1) fulfillment of certain social obligations and 2) barred the pursuit on non-normative gender roles. But not all women united in being “a woman” within these predetermined social boundaries. To the contrary, this did not mean all women united in movements for women’s rights (e.g., suffrage movements). Miscalculation of the effects of gender equality promoted speculative levels of social perversity and immorality. This persisted through the mid-twentieth century and women infiltrated the work force (of course, this is primarily middle-class women, as women in lower-classes have been forced to work for millennia). Buildings were constructed in certain socio-cultural contexts, and men and women somehow ended up with separate restrooms. In buildings where construction space is limited and few women are expected to work (do to other social obligations of the time), the women’s restroom is constructed with fewer stalls and in smaller spaces, satisfying the (falsely) projected deficiency of women in science.

Let us look at this restroom dilemma through a metaphorical lens. Laws, rules, and buildings are conceived and constructed to fulfill a certain need while inadvertently (perhaps) reinforcing cultural ethics and gender norms. While serving their purpose in a given temporal and spatial context, the protection they provide may be seen by posterity as hampered freedom. Are unisex laws and unisex restrooms what we are to expect in the future? Is this a consideration we must make in the path to gender equality?

¹Just a small example from external media to support this assumption:

Desk Set (1957)–about 3 minutes into this clip:

“Often when we meet people for the first time some physical characteristic strikes us. What is the first thing you notice in a person?”

“Whether the person is male or female.” —Bunny Watson (Katharine Hepburn’s character) 

Teresa (right) and I met in high school at the North Carolina School of Science and Mathematics. We love doing science and talking about how to make science better.

Regular readers of the blog may know that I feel strongly about the importance of skilled leadership in a lab. I believe scientists need to be taught the so-called “soft skills” that are required to be a good leader.

Last year, I recruited a team of dedicated, like-minded graduate students, and we created a class to teach ourselves what we wanted to know–what is the best way to run a lab? As we learned over the course of that semester, effective leadership is not second nature to most scientists, nor is it a mystery of the universe. There are some “best practices” for how to lead and manage that are well-known outside the academic culture, and they should be taught formally as part of a scientist’s graduate curriculum.

For this coming fall, our training program is growing into a series of talks that we’re calling Science Leadership and Management, or SLAM for short. (Allow me to pause here and give a standing ovation to John Haberstroh for his marketing genius. Who doesn’t love a good acronym?) We are preparing a stellar lineup of guest lecturers from a variety of science career paths to speak on subjects like motivating students, building effective teams, delivering feedback, and more. Our vision is that this type of training will someday be developed on a national level, to be applied at any university for any scientific discipline.

If this sounds like a good idea to you, there is something you can do right now to support SLAM. Go here to vote for our entry in the 2013 NSF Graduate Education Challenge. Teresa Lee (beloved BSR author) and I wrote an essay about SLAM for this contest, which you can read below. I’ve also included our answers to a brief questionnaire that accompanied our submission. Please vote now, and ask your friends to do the same!

Note: Registration is required to vote. After you’ve voted for us, take a look at the other entries. There are a lot of great ideas there, and I guarantee you will come away with a bit more hope for the future of science.

Tell us about your team

We are two members of a 5-person student team who decided in 2012 to organize a course at UC Berkeley on the principles of SLAM (Science Leadership And Management). Both of us had sat in on courses in organizational behavior and management, and we wondered why the same concepts weren’t being taught to graduate students in science. These courses applied a social science-based understanding of interpersonal interactions to real world problems. We were pleasantly surprised to discover that there is a wealth of data about how to best approach some common difficulties encountered by scientists. If scientific leaders learned to apply management principles to their groups, they could keep their labs running as smoothly and productively as possible. Good management helps groups accomplish a shared goal while allowing everyone in the group to achieve their full potential, and we want to share that knowledge with the scientific community.

Why are you competing in this challenge?

We have identified an unmet need in STEM graduate education. When we started our own management and leadership course for scientists, we were surprised at the number of professors and administrators that told us how valuable they thought our course would be. Our thought was, “If this training is so valuable, why should we limit it to UC Berkeley?” This challenge is the perfect opportunity to bring national awareness to the issue of teaching leadership in graduate school.

What makes your team qualified to win?

Based on our experience as researchers in training, and numerous conversations with scientists both inside and out of academia, we have devised a simple solution to a serious problem. We’ve shown that our idea can be successfully implemented, even by graduate students who aren’t experts in management. Improved leadership skills have already been useful to the students who took our course and will become even more important throughout their careers, no matter what path they follow.

Training graduate students in SLAM (Science Leadership and Management)

by Anna Goldstein and Teresa Lee

The problem

All across the country, Ph.D. programs excel at preparing young scientists to succeed in the laboratory. Students learn how to identify scientific questions, how to design and perform experiments, how to interpret data, and even how to communicate their knowledge to others. However, there is a paradox in science education: the further a scientist advances in their field, the more removed they are from the bench. The responsibilities of a research scientist, whether it is in an academic, industrial, or government setting, tend more towards leading and managing than toward active lab work. Scientists are hired based on their excellence in the lab, and are then suddenly responsible for coordinating a group of students, post-docs, and staff to conduct experimental work. Rarely does their training fully prepare them for this responsibility.

There is an urgent need for formal instruction in how to successfully navigate interpersonal interactions in a laboratory, which we call SLAM (Science Leadership and Management). As the future leaders of the scientific community, much will depend on our generation’s ability to help lab members work together effectively. The ramifications of more capable leadership even extend beyond the lab – the complexity of today’s most pressing research problems has led to increasing collaboration, including large projects like those that mapped the human genome and constructed the Large Hadron Collider. A senior researcher must have both the scientific knowledge and the interpersonal skills required to guide potentially dozens of scientists toward research success.

We are not the first to notice a serious lack of management education for scientists, and many agree it is better to start earlier in a scientist’s career than to wait and provide on-the-job training. In 2012, the National Academies held a workshop entitled Graduate Education in Chemistry in the Context of a Changing Environment; among the skills that participants identified as important for students to learn in graduate school were “Learning to manage other people” and “Exhibiting leadership” (1). In a 2012 Nature commentary, Jessica Seeliger described the challenge of adjusting to the management responsibilities of an assistant professor: “When it comes to running our labs and managing people, we have to rely on our gut feelings, our limited know-how from mentoring a few students or our observations of our previous advisers.” (2) Although there are a number of professional development programs available to graduate students and post-docs, these tend to focus on securing a position rather than performing it well.

The origin of the problem lies in the culture of science. In carrying out research, scientists prize rationality above subjectivity and expect breakthroughs to arise from the work of brilliant individuals. But increasingly, good science grows out of relationships between good scientists. Scientists are people, and people do not always react to challenges in the most rational ways. There are entire fields of social science devoted to studying the most effective ways of organizing, motivating, and managing a group to accomplish a common goal. Every business student receives instruction that prepares them to become effective leaders. With this wealth of knowledge available, why are scientists left to reinvent the wheel?

Our solution

To fill the current educational gap, graduate students in the STEM fields should receive formal training in SLAM, with a focus on specific leadership and management challenges that arise in scientific contexts. This need is neither addressed by existing curricula in Ph.D. programs nor by more general management training for professionals.

We envision a course similar to the one that we founded at UC Berkeley in 2012 with a committee of fellow students from the departments of Chemistry and Molecular and Cell Biology (MCB). We organized a lecture series where guest speakers presented on a wide range of topics, including conflict management, mentorship, and team-building. The course content grew organically from the interests of the speakers, but several overarching themes emerged. Students learned about the many different communication styles of scientists and how they impact working relationships. Speakers presented various strategies for how to resolve conflicts with employees, supervisors, and peers. They also focused heavily on the importance of clear expectations and specific, constructive feedback in keeping lab members motivated and productive.

The course enrolled 60 students, the majority of whom were in their 4^th or 5^th year in Chemistry or MCB. From midterm and end-of-semester assessments, we learned that almost all students felt that they benefited from taking the course: 18/19 survey respondents answered “Agree” or “Strongly agree” to the statement, “The ideas I learned in this course will help me in my future career.” We hope that this course will be offered yearly, and we expect it to be developed and refined over time, perhaps even becoming a requirement for Ph.D. degree programs in participating departments. Our model for this course could easily be reproduced at other universities.

Not only will SLAM training be important in the career development for any student who goes on to run a research group, it will also be immediately applicable in a student’s graduate research. The principles of successful interpersonal dynamics can be put into action right away, ensuring that students are equipped to produce successful research during their Ph.D. This type of training also has value beyond careers in research science. Strong interpersonal skills become even more useful assets if a student chooses to leave research to pursue teaching, consulting, or any number of other alternative career paths, as more newly minted Ph.D.s are choosing to do.

Some organizations have sponsored workshops targeted at scientists, like those from HHMI, EMBO, and Cold Spring Harbor. However, each of these workshops can only serve a relatively small group of people, most of whom are junior faculty. If leadership training were instead built into the structure of a graduate curriculum, early career scientists would have already had years of experience honing their skills before accepting a formal leadership position. To reach the broadest possible audience of graduate students, this type of training must be endorsed by department and university administrators, as well as federal funding agencies. The NSF should sponsor training programs and develop a standard curriculum that could be tailored to suit the needs of each particular department or field.

The class that we offered last year demonstrates how easy this idea is to implement. But we only scratched the surface of what could be accomplished by a dedicated team of educators and students, working together to map out a training course. The most effective course would incorporate skill development through interactive exercises and informational content from lectures and readings. Citations from the primary literature on organizational behavior would allow students to evaluate the utility of the skills they learn, while also appealing to a scientist’s data-driven outlook. To better prioritize which skills to address, the NSF could conduct a survey of scientific leaders to identify which skills they have found the most useful (or which skills they wish they had acquired before embarking on their career). Long-term assessment could track the success and satisfaction of the students following graduation, to determine whether this training makes a measurable impact in their careers.

The bottom line

Modern graduate education follows a centuries-old model of apprenticeship, which has not kept up with the evolution of scientific research. Research groups now resemble small businesses, where the principal investigator must fill many roles: supervisor, mentor, teacher, manager, publicist, and fundraiser. Even those with the best of intentions cannot lead effectively if they have not been exposed to good management practices.

Scientific research fuels innovations that are immensely valuable to our society, like in the areas of information technology, renewable energy, and life-saving medicines. It is a tragic waste of resources to tackle these goals without creating a workforce that is as efficient and well-run as possible. As it stands, researchers are left to discover effective management strategies by trial and error. With so much funding and effort invested in each individual graduate student, why should we leave their leadership development to chance? By including the SLAM skillset in scientists’ graduate training, we will generate more effective scientists and faster scientific progress.

References

1. Committee on Challenges in Chemistry Graduate Education; Board on Chemical Sciences, Technology; Division on Earth, and Life Studies; National Research Council, Challenges in Chemistry Graduate Education: A Workshop Summary (The National Academies Press, 2012).
2. Jessica C. Seeliger, “Scientists must be taught to manage,” Nature 483, no. 7391 (March 28, 2012): 511.

Recently I’ve been contemplating giving up on the modern world and moving to a cabin in the woods. I mean – what is with all of this technology, the 50+ hour work week, and guilt over the simple pleasures like spending time with friends and family on the weekends? Maybe I would be able to feel happier and more fulfilled if I turned my back on the world of today and instead started living a simple life. After all, despite the fact that technology has made our lives easier over the past century, people do not report being happier than they were before smart phones, computers, and the internet.

Picture it – a cabin in the woods next to a gurgling river, a garden out back with beautiful flowers and delicious produce, a feeling of being close to nature, like my ancestors. More time for important social interactions, which are really at the heart of a meaningful life. No more random interneting or hours spent ignoring my husband in favor of my smart phone. Instead I’ll spend my days doing meaningful things, going to bed with the setting sun and sleeping as much as I need. Really, imagine it. Don’t you all want to come and join me in the woods?

But would I really be happier if I gave up modern conventions and moved to an isolated cabin? Up until a few hours ago, I really thought that might be the solution. But then I read an article by a 26 year-old, Paul, who had given up the internet for a year. He felt that the internet was preventing him from figuring out who he truly was, and it was time to take back his life and his identity. And giving up the internet was good – for the first few months. He spent more time with friends, used his boredom to write more and explore his creativity in other ways. He read more and went out more. But then Paul adjusted to not having the internet and soon found himself developing bad habits offline. He was unable to keep in touch with people who were far away, and his snail mail began to overwhelm him until he was unable to cope with sending responses to his fans. The moral of his story – we are who we are and we will be who we will be, internet or no internet.

This really got me thinking: would I actually be a better person if I lived in the woods? Would I really spend more time with my family and working on creative and fulfilling tasks? Would I actually garden more if I didn’t feel like I had to work all day and night? Or would I find other ways to fill my time that felt just as unproductive and unhealthy as random interneting? Would I find myself bored without the intellectual stimulation of a job?

Paul’s experience reminded me of the research on affective forecasting. Just as the name suggests, affective forecasting refers to our ability to forecast how we will feel in the future, or how other people feel. And it turns out that we are not that good at it. We focus on the wrong features of the situation, considering only the good, essential aspects and ignoring those other little realities – such as how inconvenient it might be to have to drive a long distance out of the woods in order to reach civilization. Or how annoying the bugs in the woods might be (I hate bugs).

I also forget that although I will be in a cabin in the woods, living a life with no internet, I will still be me. So those habits that I have now, good or bad, will come with me wherever I go. If I move to a cabin in the woods, my desire to distract myself in the morning with some form of easy entertainment instead of getting out of bed and starting my day is not likely to disappear – I will likely just end up trading a book for my smart phone. This suggests that while there may be objective features of living a simple life that agree with me, it is not likely to be the picture-perfect vision I’ve made it to be in my head.

Other research suggests that we have a tendency towards homeostasis. That is, although we may experience fluctuations in our feelings of happiness and contentment, we generally tend to fall back to our baseline status quo. So while a new experience might bring you a lot of pleasure in the moment, you will likely find yourself returning to your usual levels of happiness when the novelty wears off. Because of the drive towards homeostasis, it is the tendency of humans to habituate to the good (and bad) things in our lives (which is why a near miss feels so good). As Paul found out during his internet-free year, the excitement and pleasure at being offline wore off within a few months. I’m sure we’ve all had similar experiences with the fall from extraordinary to ordinary (perhaps with a new job, house, or relationship?). These findings suggest that I might benefit from spending a summer living in the woods, but I may find myself feeling just as irksome about life after a year in the woods as I do in my comfy house in the middle of civilization.

Finally, recent research shows that we experience more variability in happiness from day to day than we do from person to person. So maybe I’ll be more successful at increasing my happiness if I focus on making small changes to my daily life, rather than giving it all up for the “simple life.”

So what’s the bottom line? Would I be happier if I got away from the pace, demands, and technology associated with modern day life? I honestly am not so sure. But all of this research does make me think that perhaps as long as my basic needs are met, how I feel inside is going to be a bigger determinant of my happiness than any external factor such as the view from my window.

Am I the only one who contemplates giving it all up and go live in the woods? Do you think I’d be happier if I did?

More Reading:

Wilson, Timothy D., & Gilbert, Daniel T. (2003). Affective Forecasting. Advances in Experimental Social Psychology, 35, 345-411 DOI: 10.1016/S0065-2601(03)01006-2

These upcoming funding, conference, and award deadlines are focused on the graduate student audience; however, many may also apply to postdocs, undergraduates, or young faculty as well. Profiled below is funding to attend the Green Chemistry & Engineering Conference, the American Chemical Society (ACS) Meeting, a grant for public outreach of Analytical Chemistry, an Organic Chemistry Graduate Fellowship, and the ACS Western Regional Meeting.

1. NSF Student Travel Scholarship for the Annual Green Chemistry & Engineering Conference

The National Science Foundation (NSF) is offering a travel grand up to $1,000 for the 17^th annual Green Chemistry & Engineering (GC&E) Conference in Washington, D.C. from June 17-20, 2013.

- Deadline: May 20, 2013

- Submission Link: http://gcande.org/students/nsf-student-travel-scholarships/?cid=email_gci_direct_5_7_13

- Eligibility: Undergraduate, Graduate, and Postdoctoral current students

2. ACS Entrepreneurial Training Program (ETP)

For scientists interested in entrepreneurship, ACS is partnering with the Kauffman FastTrac program for an Entrepreneurial Training Program (ETP) for scientists. FastTrac helps guides scientists to move from concepts to products and markets and provides training related to intellectual property, founder transition, and equity financing. Business ideas are required for submission.

- Deadline: May 28, 2013

- Submission Link: http://surveys.acs.org/se.ashx?s=04BD76CC113B305D

- Eligibility: All chemists interested in entrepreneurship

3.   Young Chemists Committee Travel Funding to an ACS Meeting

The ACS Young Chemists Committee (YCC) and the CIBA Foundation award $500 travel grants to young scientists to go to and present at an ACS national or regional meeting. This award is twice a year, with July 1 and December 31 deadlines.

- Deadline: July 1, 2013

- Submission Link: http://webapps.acs.org/findawards/detail.jsp?ContentId=CNBP_027188

- Eligibility: Under 35 years, current Postdoc or within first 7 years of professional career

4.  ACS Division of Analytical Chemistry

In celebration of their 75^th anniversary, the ACS Division of Analytical Chemistry is offering $500 grants to projects to promote the history and impact of analytical chemistry. These projects can be a plenary lecture or symposium or an activity involving the general public. This seems like a great opportunity for an school or organization to host a visiting analytical chemist!

- Deadline:  June 1, 2013

- Submission Link: http://www.analyticalsciences.org/ANYL75projectrfa.pdf

- Eligibility: Chemists participating in analytical chemistry related outreach activities

5. ACS Division of Organic Chemistry Graduate Fellowships

The American Chemical Society Division of Organic Chemistry is offering fewllowships for 3^rd and 4^th year Ph.D. students in Fall 2013. The fellowship is $26,000, which includes $750 for travel to the 2015 National Organic Symposium to present a poster. Only one application per research group will be accepted.

- Deadline: May 31, 2013

- Submission Link: http://www.organicdivision.org/?nd=graduate_fellowship

- Eligibility: Ph.D. students starting their 3^rd or 4^th year in Fall 2013

6. ACS Western Regional Meeting, Co-hosted by the California and Santa Clara Valley Sections

The 44^th Western Regional Meeting will be held October 3-6, 2013 in Santa Clara, California. The Call for Papers and Registration are currently open. Plenary speakers include Priestley Medalist Dr. Darleane Hoffman (Berkeley and LBNL) and the Cope Scholar Symposium in honor of Dr. Sarah Reisman (Caltech). The conference will also feature career development and leadership development workshops, and the regional awards banquet.

- Deadline: August 23, 2013

- Submission Link: www.wrm2013.org

- Eligibility: Chemists, all levels

Photograph courtesy Decaseconds Photography.

Hi Barreleye!

Now, I want you all to stop for a second and look at the picture above.  Notice anything strange?  That’s right—the fish’s head is transparent.  And those two globular things inside: no, they’re not its brain, they’re actually the fish’s eyes.  While the creature’s existence has been known for a while, researchers were recently able to capture a Barreleye on video with some pretty sophisticated deep-sea exploration.

The Barreleye (also called a Spookfish) needs to cope with the fact that sunlight can penetrate through water only so much.  As a result, the amount of light that makes it to the depths of the sea is incredibly small.  However, fish still need to be able to see in order to navigate, find food, and escape predators, so nature has equipped them with two massive light-sensing eyes that point directly upward.

The eyes are completely filled with so-called “rod” photoreceptors.  These are a type of cell that will respond to very faint amounts of light.  Because they are so sensitive, these photoreceptors will allow the Barreleye to detect very small changes in light from above.  This is useful in spotting the silhouettes of food or predators.  These two eyes are embedded within a translucent membrane that keeps the delicate cells safe as the animal steals food from the stinging tentacles of man o’ wars.

But it doesn’t stop there.  A recent paper discovered that the Barreleye’s visual system is much more complicated than that.  You might be thinking that seeing upward sounds very useful, but what about what goes on down below?  There’s a lot of important activity coming from the depths of the sea (for instance, from bioluminescent creatures on the ocean floor).  In order to cope with this, the Barreleye actually has another set of eyes.

A/B show the fish from the top, and C/D show the fish from the bottom. The colored parts are the fish’s eyes.

The image above shows a top (A/B) as well as a bottom (C/D) view of the Barreleye fish.  In particular, note that there are two little colored circles on the bottom of the fish’s body.  These are the openings that the fish uses to see beneath itself.  However, rather than being pointed straight down, the second pair of eyes use a complex system of mirrors to reflect light from below onto another retina.  Look at the white arrow in D…notice that little which patch?  That’s the series of mirrors that the fish uses in order to focus light from beneath.

This is the Barreleye’s eye from the front.

Now take a look at the picture above.  This is a slice of the fish’s eye, if the camera was facing the fish’s front.  Notice that there are two chambers here…the big one on the right is for the giant, upward-facing eye, and the tiny one to the left is for the reflective eye that looks downwards.  That little line of purple labeled “m” is a series of mirrors, each of which is oriented at a different angle.  Just across from these mirrors is a second retina (labeled “dr”).

The Barreleye has two retinas to detect light from both below and above.

Light passes upwards from below, hits the mirror, and is then reflected across the smaller chamber to the retina.  This allows the fish to focus on images beneath it, as well as to detect what’s going on above.  On the right side, light comes in from above, and is focused by the large cornea onto the retina below.

Using this combination of light-bending biology, the Barreleye is able to both detect incredibly faint movement coming from above, as well as the bioluminescent life down below.  In its array of tools the Barreleye has managed to evolve not only a giant transparent dome to house two large “telescopes” that point towards the surface, it also contains a complex array of mirrors to focus light from below.  All this from a tiny creature that gets most of its food by stealing from jellyfish.

Nature often solves problems in incredibly elegant ways, and the fact that it does so with the brute-force of gradual evolution and natural selection is truly an amazing feat.  While we spend most of our times thinking about what lies beyond our own planet (or in my case, what goes on between our ears), we would do well to remember that there is still a fascinating unexplored universe that lies all around us.  Whether it be in the sea or on land, this planet contains countless numbers of unexplored nooks that are brimming with wonderful creatures and amazing discoveries.

source

When I was younger, I can remember being split into teams in gym class and different tables in art class and having one question: how many girls and how many boys are in my group? Depending on the activity, it seemed important to know this so you could assess your chances for success. More boys on your team, and you might be more likely to win dodgeball. More girls at your art table, and you might paint a better mural.

An adult might have told me that was silly – how many boys vs. girls were in my group didn’t matter. However, recent research suggests that the gender composition of a group does matter. Though it doesn’t matter in terms of impacting actual performance, it can influence how group members think about one another and about their group as a whole. Because I love research that examines people in their natural (or somewhat natural) environments when they are interacting with other people, let’s take a look at how the researchers demonstrated this.

To study how groups are evaluated based on their gender composition, social psychologist Tessa West and colleagues created 5-person groups of management students who had recently met. Some of the groups had 2 women and 3 men, some had 3 women and 2 men, and some had 4 women and 1 man. The groups were all in the same classroom at the same time, and they were asked to complete a male-typed cooperative task together as fast as they could.

source

After completing the task, each participant was asked to evaluate his or her group mates, as well as the group as a whole. Results showed that there were no differences in performance on the task as a function of gender composition: groups with more women in them did not perform any worse than groups with more men in them. However, as the proportion of women in the group increased, participants rated their own group members more negatively, regardless of the gender of the members. In addition, as the proportion of women in the group increased, the less effective participants thought their groups were – even though gender composition did not predict performance.

Ten weeks after completing the cooperative task, participants were asked how interested they were in working with their group again. Overall, people who remembered their group performing better were more interested in working with their group again. Even when adjusting for this effect, though, as the proportion of women in the group increased, the less the group wanted to work together again when asked at this ten-week follow-up.

One of the interesting aspects of this research is that it is not outsiders who are evaluating men more harshly when they are in groups with more women. Instead, men and women within the groups are judging their own group mates more harshly when their groups have a greater proportion of women.

source

Why does this happen? It may be because of a process known as stigma-by-association.This occurs when the stigma associated with one person spreads to an associated individual. For example, if a thin man were married to an overweight woman, the stigma attached to the woman because of her weight (e.g., that she is lazy) might also “leak” to her husband. By being associated with her, others might also perceive him as being lazy. When it comes to gender, we are all familiar with stereotypes of women as being less efficient and less competent than men, especially on male-typed tasks. For a male/female pair in the workplace, then, the man might be evaluated as less competent (due to his connection with a female) than had he been working with another man.

This work highlights a potential, unintended consequence of diversity in the workplace. In the future, the researchers are hoping to disentangle whether these effects are due to different behaviors of men and women (e.g., more talking during the task) or to differences in perception of men and women. Hopefully, by demonstrating that bias can operate in this hidden way and affect groups and not just individuals, researchers can figure out how to ameliorate these effects.

Reference:

West, T., Heilman, M., Gullett, L., Moss-Racusin, C., & Magee, J. (2012). Building blocks of bias: Gender composition predicts male and female group members’ evaluations of each other and the group Journal of Experimental Social Psychology, 48 (5), 1209-1212 DOI:10.1016/j.jesp.2012.04.012

Tom Brady is no stranger to pain (source)

Every Wednesday afternoon, I gather with a bunch of faculty and graduate students at the University of Illinois to discuss a journal article about social psychology, and to eat a snack. This blog post reflects the discussion we had during this week’s seminar affectionately called Social Wednesdays and Grub (SWAG).

This week in SWAG we read an article about racial biases in perceptions of others’ pain. The American medical field has a long history of racial bias (Note: I think if you switched the words “medical field” with almost any other field, the sentence would be factually accurate. For example, “mathematics field” or “psychology field” but not “magnetic field”). American blacks tend to be diagnosed less accurately by medical staff than whites, to receive less optimal health care, and to be cared for less intimately. The authors, led by Sophie Trawalter of the University of Virginia, wondered about the source of this racial bias. They reasoned that it might arise in part from a belief that low status groups experience less pain than other groups in society. Blacks and other traditionally low status groups in America are perceived as having overcome greater hardships throughout their lives. As a result of contending with, and overcoming these hardships, low status groups are perceived to experience less pain than their more advantaged counterparts—their tough circumstances have made them tougher. This racial bias in pain perception is theorized to underlie the black-white treatment gap in medicine.

The authors tested this pain perception bias in an interesting way: In the first study, the authors examined injury reports made by the NFL. Injury reports are the fixation of fantasy football armchair quarterbacks everywhere, and they are frustrating largely because there is a great deal of error in how different teams report injuries for specific players. Teams categorize players with increasing levels of play likelihood based on a reported injury—with players labeled as “probable” more likely to play than players labeled as “questionable” or “doubtful.” The severity of team reported injuries is surprisingly independent from whether a player actually plays the following week. The authors wondered if there exists racial bias in the errors in these NFL injury reports such that black players are reported as more probable than their white counterparts, despite having the same injury.

Examining injuries that ranged from lacerations, to knee injuries, to stingers the authors found evidence for race bias in NFL injury reports: Specifically, black players were categorized as more probable than their white counterparts despite having the same type of injury.

In the remaining experiments, the authors sought causal evidence that race influences pain perception bias. They presented participants with a number of black and white faces that were pretested to be rated as similar on a number of attributes (e.g., emotion expression), and then asked participants about how much pain the target in the photograph would experience during a list of physical injuries like “having a tooth pulled.” The authors found that black faces elicited perceptions of reduced pain relative to their white counterparts to the same physical injuries.

In the final experiment, the authors attempted to link this racial bias in pain perception to social status. Participants were asked to imagine a person in a photograph (manipulated to be either black or white) who was low status, equal status, or high status within one’s workplace, and then to judge that person’s pain experience for the same list of physical injuries. In this analysis, status captured all the variance in pain perception: Imagined low status targets were perceived to experience significantly less pain than high status targets, presumably because low status individuals have overcome more hardships throughout their lives, and are tougher as a result.

I think SWAG enjoyed reading this article. One of the nice things about it is that it attempts to do what is the main goal of social psychology in my view—examine a phenomenon like racial bias in medicine with the goal of uncovering the specific reason(s) why this bias occurs. Testing the phenomenon with actual NFL injury data that both real athletes and armchair athletes care about is another positive because it engages a real issue with implications for the health of real individuals. Race bias in NFL injury reporting could put some black NFL players at greater risk of sustaining worse injuries or exacerbating existing ones.

SWAG had some questions about the data analyses throughout the studies—for instance, it’s not clear how the researchers analyzed the NFL data (Note: Because the study was published in PLOS one and the journal allows post publication comments, I went ahead and asked the authors about providing more data analysis details. I hope this will generate a response!). Still, it was exciting work and we couldn’t help but think up a number of different experiments to follow those presented in the paper. The article made us all excited about social psychology… and donut holes… the jelly filled ones in particular.

References:

Trawalter S, Hoffman KM, & Waytz A (2012). Racial bias in perceptions of others’ pain. PloS one, 7 (11) PMID: 23155390

This year we will be joined by Edwin Dobb, former senior editor and acting editor in chief of The Sciences, a publication that has been the recipient of numerous National Magazine Awards, and is viewed by many as the best general interest science magazine ever published in the U.S.  An independent writer for more than 20 years, Dobb has written about the environment and many other topics for Discover, Audubon, Mother Jones, and The New York Times Magazine, and many others. For several years, he was also a contributing writer at Harper’s.

Dinosaur Lives, by John Horner and Edwin Dobb

Dobb is the co-author of Dinosaur Lives, which The New York Times selected as a notable book of the year and The Los Angeles Times picked as a best book of the year. His work has been anthologized in The Best American Science and Nature Writing Series. Dobb is also the co-writer and co-producer of a documentary film about the social and environmental consequences of industrialized copper mining. Called “Butte, America,” the film was screened at festivals across the U.S. and overseas, and was broadcast nationally on the PBS series Independent Lens. 

In addition, Dobb has written TV treatments for WNET, New York and George Lucas & Alvin Perlmutter Productions. Since 2000, he has been a part-time lecturer at the U.C. Berkeley Graduate School of Journalism, teaching magazine writing and environmental journalism. Currently he is the Carnegie Lecturer in the Knight Program in Science and Environmental Journalism. Dobb is also a feature writer for National Geographic.

What does it mean that, “My computer can do what your computer can do?”  My computer can play Crysis, and yours probably can’t, but is that really a meaningful distinction?  My computer has a bunch of ports and things on it—USB, HDMI, etc.—and there’s probably a bit of overlap between my computer and yours there.  But my computer could be missing most, if not all of its ports, and it could definitely still be said to compute.

You might have a Mac, and I have a PC, but again, that seems like a superficial difference—while there may be certain programs that only run on PCs and not Macs, it’s not like a similar sort of program couldn’t be written for a Mac that did the same thing.

We could play this little reductionist game all day—winding down past the processor of the computer, comparing flip-flops and NAND gates, past transistors, down to the electrons themselves—those tireless carriers of the binary alphabet of our information age.

But what’s the difference between electrons carrying out computations versus me carrying out a computation?  After all, given enough time, I (or perhaps, Suzie) could manually reproduce anything either my or your computer is capable of computing.  We’d just have to follow the correct rules (and possess a sufficient amount of paper…and pencil lead).

Unfortunately, this has brought us no closer to defining this idea of equivalent computational power—all that we’ve decided is that we are at least as computationally able as our own computers!  But this is a subtle sort of computational equivalence—it has nothing to do with speed, as the CPU on a modern processor carries out in the ballpark of a few billion operations per second, and you or I can probably carry out somewhere in the ballpark of one per second.  Further, it has nothing to do with representation—be the computational substrate electrons, lead, rocks, or water, we don’t care so long as the procedure can be replicated and carried out to yield an equivalent result.

It turns out that there is a wonderful (and precise) formalism for this idea of equivalence which was developed long before there was anything like the modern idea of a computer, and it came from the grandfather of computing himself, Alan Turing (for a glimpse at Alan Turing’s tragic life, see here, and for a less tragic entertaining fictional depiction, see here).  Turing called them a-machines, but the idea is now known as a Turing Machine.

The formalism, which I’ll sketch shortly, seems a bit strange at first glance, but the real power of it is that any computing device can be reduced to a certain type of Turing Machine.

So: Imagine you are seated at a table, and in front of you is a long, segmented strip of paper and a pencil.  One end of the paper extends (countably) infinitely far to your left, and the other, infinitely far to your right.  You might imagine the segments as being lines, as if on lined paper, except the lines are going top to bottom instead of left to right.  One particular line of this infinitely long strip of paper is the focus of a magnifying glass in front of you.

On your lap is a leatherbound book suggestively entitled “PROGRAM”.  Upon opening it, you see there’s a long table, and each line looks something like this:

• IF SEGMENT READS ‘B’ AND YOU ARE HAPPY, REPLACE WITH CHARACTER ‘A’, SHIFT TAPE TO THE LEFT, AND BECOME DESPONDENT.

With some limited variation: sometimes the ‘B’ in first clause and the ‘A’ in the second clause are other characters from some finite collection (say the alphabet), including ‘blank’ and a special character called HALT.  The third clause sometimes might say to shift right instead of left, or perhaps not shift at all, and the emotions of the first and last clause always come from a finite list (despondency, happiness, anger, etc.).

After some rumination, you notice that the table is also self-consistent—there’s no two entries on the table that could ever both apply to the same configuration of your emotional state and the reading on the strip of paper.  Further, there’s always one and only one thing for you to do to the strip for any given combination of characters-under-magnifying-glass and emotional states.  Lastly, you surmise that the character to be replaced is the character upon which the magnifying glass currently focuses.

So, you set out following the program—writing characters, shifting the strip of paper back and forth, erasing characters, and schizophrenically altering your emotional disposition upon command of your leatherbound overlord.

Eventually, you come across that peculiar HALT character, and you stand up to inspect the strip of paper.

And it occurs to you that the paper now contains the first million digits of Pi.

Up to some technical considerations, you have just implemented a Turing Machine!  But not all Turing Machines are the same—as I said, they are typified by some specific finite alphabet, and some specific finite set of mental states.  It turns out that what any specific Turing Machine is capable of computing is strongly dependent on the number of characters in its alphabet and the number of emotional states that it can cruelly instruct you to emote.

A two-state, two-character Turing Machine is not terribly interesting.  With patience, you could probably figure out every “computation” such a device was capable of performing.  One heuristic way of quantifying this is finding the maximum number of steps any given program will run on that class of Turing Machine before a HALT given a completely blank starting strip of paper (that it be initially blank is important).  Notice that it’s straightforward to create a Turing Machine that never reaches the HALT command.  You just feed it a blank sheet of paper and the command:

• IF SEGMENT READS ‘BLANK’ AND YOU ARE ANGRY, REPLACE WITH CHARACTER ‘BLANK’, SHIFT TAPE TO THE RIGHT, AND BECOME ANGRIER.

Thus you will become angrier and angrier, and the Turing Machine will never HALT.  But it must be true that, if a Turing Machine is going to HALT, it will always do so after some maximum number of steps.  And it just so happens that if a two-state, two-character Turing Machine is going to HALT given some program and a blank input, it will do so in 6 steps (proving this is actually a little nontrivial).  Such a number is innocently dubbed a Busy Beaver number, and was introduced by Tibor Rado in the 1960s.

Thus, a two-state, two-character Turing Machine fed a blank input won’t ever tell us anything more interesting than can be specified in about 6 binary characters (it’s actually a bit worse than this, as a two-state, two-symbol Turing Machine will only ever write at most 4 of the same type of non-BLANK characters on to the strip of paper before it HALTs).

So what makes for an “interesting” Turing Machine?  Well, if you modestly increase the number of characters to 6, and the number of states to 4, two very important things happen.

First, we have no idea what the Busy Beaver number is for such a machine.  It’s at least 1.3 × 10⁷⁰³⁶, but in reality significantly larger than that (for reference, this number is about 10⁶⁹⁶⁰ times larger than the number of atoms in the observable universe—it’s one of those numbers that’s so large, it’s hard to actually articulate how large it is).  In fact, even if you got your hands on what this number might be, the proof of its truth might be independent of Zermelo-Fraenkel Set Theory.

Secondly, such a Turing Machine can simulate any other Turing machine, including Turing Machines with more characters and more states.  Such Turing Machines are called Universal.

The specific schemes demonstrating exactly how such a thing is possible are, in general, rather complicated.  But the result is dramatic: any program that you or I run on one of our computers that takes an input and registers an output can be cast on and evaluated by a 6 character, 4 state Turing Machine.  Remember that we required that the starting input be blank.  If we relax this constraint, there’s a somewhat controversial claim that even two state, three symbol Turing Machines can be made universal.  The controversy arises because it becomes difficult to disambiguate the complexity of the Turing Machine from the complexity of the specific encoding scheme  used to initially prime the strip of paper with symbols.

The interesting results only start here: in part 2b, with this idea of computational equivalence in hand, we’ll flesh out this idea of computability a bit further.  And finally, we will encounter the Russian.