I tackle socially-relevant questions and compare different methodological approaches to answering them. These posts will highlight particularly interesting methodological and conceptual developments from a variety of disciplines. They will also tackle specific social “problems” – such as partisanship’s effects on political communication.

My specialities are social psychology, communication, and cultural anthropology. The former emphasizes rigorous statistical training and the use of subtle experimentation to identify key variables for understanding human behavior. You may have heard of a “crisis” in our discipline. I prefer to think of it as growing pains – we are acknowledging the limitations of our tools and moving towards both greater caution and greater accuracy in interpreting results.

Dealing with the complexity of human behavior is difficult. We are unable to have the same level of certainty that a physicist or chemist may have (and even drug companies have had great trouble replicating key, published and oft-cited, findings in their field). In order to detect a reliable pattern that is consistent across situations, the best human-behavior studies would have hundreds or thousands of people, a practical difficulty that is only occasionally surmountable.

All is not lost, however. Even a smaller study can highlight an important relationship between different factors. At that point, it’s the field’s duty to conduct more research, replicate or fail to replicate the result, and to try to understand whether the initial result was due to chance or due to a third variable that moderates (that influences the strength of) the effect.

Looking from an interdisciplinary perspective, however, we can be inspired by laboratory-studied relationships and look for independent evidence of their relevance to “the real world.” The laboratory allows us to take a micro-view, to get at what people can’t or won’t tell us about themselves. We can then take these findings to the field and look for evidence for or against the laboratory results.

As a cultural anthropologist working with the Maori, New Zealand’s indigenous people, I was keenly aware of the fact that my cultural narratives, as well as the narratives the Maori used to describe themselves, drove the questions that I asked. I was able to ask questions that pitted these potential interpretations against one another and to record the response of individual Maori informants. Were they skeptical of the narrative? Did it make sense to them? What was their emotional response? Were some members of the community more open to my account than others? Were they open to the account, but did it strike them as novel? These are all questions an anthropologist asks.

Combining social psychology and cultural anthropology we can become more attune to the unobserved factors that inform human behavior. Are people, for example, publicly advocating a narrative of which they are privately skeptical, or at the very least, feel neutrally about? Translating social psychological findings to the field, we can make predictions about the gap between how people will see themselves, how they present themselves, and what may actually be motivating their behavior.

It is in the tension between insights that we often make the most progress.

Sound wishy-washy? Studying human behavior requires working with ambiguity, at least if you’re interested in having both descriptive and predictive validity. Descriptive validity concerns mechanism; predictive validity emphasizes outcome. For better or for worse, shaping the world in innovative ways requires an attention to both process and product, the navigation of multiple approaches, and a willingness to investigate and to challenge our most basic assumptions in a systematic way.

In the end, we all do the pragmatic thing. We all choose a side, take a stance, and act. However, we can do so humbly, aware of complexities, without blinders. We can do so boldly, honestly, and in a way that convinces others that we have selected the best response given what we know at the time.

Ok – the last step, being humble, bold, and yet persuasive to an audience that wants simple answers, is more difficult. Fortunately, both anthropology and social psychology offer important insight into how to communicate complexity and yet provide stability, knowledge, and purpose.


Statistical Thinking Can Organize Qualitative Analysis

W/ my co-presenter, I conducted a whirlwind tour of complex regression models (serial mediation, parallel mediation, multi-level models, and multi-level mediation) to our lab. If you can imagine it, and you have meaningful quantitative data, there’s a model for you! (even if you only use SPSS, there are macros – PROCESS and MLMED) for you.)
When I was driving back from visiting my parents in Raleigh, one of the things I really looked forward to in Columbus was my multi-level modeling class (finding patterns in data when your observations are clustered within an individual, country, media market, school, etc). I was excited to be acquiring new tools – new ways of tackling meaningful questions, systematically. Knowledge is power (limited power, sometimes, but power none the less). 
Statistical tools are not only powerful for measuring complex social situations, but can be powerful for thinking about them as well. I like to joke that stereotypes reflect really simple statistical thinking (mean differences). Intersectionality starts to take different levels of variables into account (regression). Privilege demands thinking in terms of clustering – different people with different traits in different situations (i.e. multi level regressions).

How many articles have you read on topics like privilege that had no guiding framework for thinking about the influence of group-membership, individual traits, overlapping groups, and categories of situations? They tend to fumble. They try to simplify with analogies, but often that simplicity feels artificial. Multi-level regression provides a heuristic framework – a way of organizing how we tackle that complexity. Even if we lack the data for a conclusive analysis – multi-level modeling helps us to articulate our questions, our guesses, and our insights.

It is also something, as the presentation this morning indicated, that can be made accessible in qualitative terms. 


Things to keep in mind when thinking about police shootings . . .

Things to keep in mind when thinking about police shootings:

Police show considerable race-weapon stereotyping, and race-aggression stereotyping on the social-psychologist designed “shooter task” – other people show even more (Correll and colleagues’ work).
Everyone has to resolve ambiguity – that’s when stereotypes can creep in. Is that a gun or a wallet? Is that person aggressive or scared? It could even lead to sensory distortions under high stress conditions. Anyone who has ever been really nervous knows to watch out for this (as opposed to blindly acting upon it). For a more everyday example of a sensory distortion, ever misread something while copy editing? Your brain “filled in the gap” with a coherent story, and the typo remained, unseen. 
Police departments are not known for cultivating good mental health – but someone with a gun acting out poor mental health is a problem across the board – whether they’re killing themselves or killing someone else.
Citizens have less experience coping wth spikes of fear – of adrenaline and cortisol – than police, who have been through training, do.
White citizens are more likely to call cops on black citizens doing “ambiguously criminal” behaviors. Cops, then, are more likely to be monitoring for “suspicious black people.”
Studies of police-driver interactions at traffic stops often see the the citizen’s reactions – perfectly at ease versus even politely defensive – leading to more controlling attitudes from police. It would be hard for citizens who have been targeted to ever be perfectly at ease. Heck, even I’ve been harassed by customs agents and police for “looking nervous”.
Mentally ill people are particularly likely to become targets – because any not perfectly “safe and predictable” behavior is interpreted as a threat. This is why some departments call in specialists who are better able to assess the situation when mental illness is suspected.
Police, like the rest of us, like their stories – even ones that are more a matter of faith than fact. You can also imagine that departments would vary by how often they actually deal wth threat. On the low end, they may, on average, be looking for an opportunity to “suit up,” at the high end the may live, on average, in a state of chronic stress and fear. 
Statistically – we can control for a lot of things – including actual-race-based difference in weapons charges and other signs of real versus imagined racial differences in dangerousness. Stereotypes are likely still relevant, even after those things are controlled for. This makes sense, empirically. We apply schema – ideas about the world – to resolve ambiguity all the time (the typo example). The solution would seem to be better schema and better methods for gathering information in the moment (both better schema and better attempts at evaluating the situation are part of the training that specialized mental health responders have).

However, statisticians, particularly ones relying on observational data, can cherry pick which measures they include, and which they exclude. They are also often trying to “start a conversation” with others in their field, such that national attention may be secondary. Sometimes “starting a conversation” means generating controversy. Even academics engage in PR, albeit for a limited audience.

So always ask yourself “Would I expect to see a race-based difference if the neighborhoods, suspects, or the officers were matched on a different set of characteristics? Statistics don’t provide the final answer, only pieces of the puzzle. To know they fit together, you have to look at them closely.

In the end, however, most statics are asking:

“Is there an average difference in y as we go up one unit on x, constant across (controlling for) levels of these other variables?” Y, for example, could be likelihood of getting shot, a one unit change in x could be going from “white, coded as 0, to black, coded as 1.” That would be a categorical variable. It could be that when people are matched on income, education, etc, a racial difference disappears, remains, or even increases. This is called “controlling for” or “adjusting for” those variables.

Often, the statistician (and you) could ask, does the odds of getting shot when black versus white depend upon another of those other variables, so that if that variable, W, let’s say, is high, the difference in Y (odds of getting shot) as X goes from 0, white, to 1, black, is bigger (or smaller)?” So if “W” is median income – it could be that the odds of getting shot while black versus white is lower in areas with high median income, controlling for (holding constant) the percentage of black people living in that area.

So many questions can be asked (and partially answered) with statistical models! The mechanics may seem complex, even scary, but understanding what a model is trying to evaluate, and how it works, is not rocket science. Like a jigsaw puzzle, it requires patience, but you can get it done!

If you want to try your hand, think about the following and try to break it down into primary relationships (outcome variables versus focal predictor variables, control variables, and moderators (if any):

Police shootings involve a rich if terrible tapestry of factors.

However, if you’re talking to any every day person, and they are feeling a sense of concrete personal danger, why not tend and befriend first, discuss and debate second? 

Separating Empathy from Action

Observing my reactions to news of terrorist attacks:
a flash of empathy
a need for action
gratitude for my own safety
gratitude for a lack of urgency
knowledge that constructive action is difficult
an empathic connection with other massacres throughout history
an openness to knowing other people’s pain.

As humans, and as researchers, we can value understanding other peoples’ experiences, even when that understanding is concomitant with our own relative powerlessness.

Quick and Cursory Look at Learning Styles


This article argues, and I agree, that individuals do indeed process information differently. There are a variety of reasons for those differences, however, only some of which are rooted in personality.

Others are rooted in process. Someone who has less experience with processing information verbally is often less good at doing so, in the short term. This difference can go away if you target their verbal learning.

Someone who has little experience with a new set of concepts may need to start thinking about things concretely, building up to abstractions. Unmentioned in the article, some may prefer to stay “abstract” because working out concrete implications feels difficult. I used to be that student.

People will have distinct strengths and limitations. But these limitations are best revealed only after someone has consistently tried, with effective instruction, and failed. Even if they persist in failing, however, they will learn and grow in the process. It can be, in the language of Robert Bjork, a memory researcher, a desirable difficulty.

Reading an Article – Advice

I recently came across this on my Facebook feed:

It is a great example of what happens when you allow a headline to make you curious, about methodology as well as topic. Dig deep, and you may uncover misleading, questionable, or just confusing decisions made by researchers and people reporting on the research. Sometimes this is deliberate, an attempt to influence the policy decisions of people who don’t have time to understand research.

However, in order to get appropriate attention, portions of almost every empirical article you see will be hyped. The introduction, sometimes, the abstract, sometimes the discussion too, will inevitably exaggerate what the researchers actually found. Those sections are designed to say “Hey, if our interpretation is correct, these results will be really interesting.”

A social scientist reads the abstract and skips right to the manipulations (what the experimenters presented differently to different people) and the measures (what they measured). That’s the concrete, meaty detail. That’s the difference between being told a movie fits in a certain genre and watching the actual movie.

Then, we look at the statistics, acknowledging that these estimates (models designed to uncover an average trend amidst all that variation) are the best they researchers could do with the tools they had. (Let’s assume they were researching in good faith). We ask questions about what they didn’t report (word limits), what they might have found but not been able to tell a clear story about (there’s a lot of messiness, even scientists like to read about clarity).

If we’re really good at statistics, we may even look for mistakes. Peer reviewers who act as gatekeepers for academic journals are generally unpaid and overwhelmed. Mistakes happened.

Then we check out the discussion (the “let’s get real” section of the paper). Then we skim the intro for any novel interpretations of the existing literature, or citations we were unfamiliar with.

This is a good approach, not just with academic papers, but with anything. What does the real evidence look like? Are people interpreting it in good faith? Are they making errors you can help correct? What other interpretations could you offer?

Applying Psychological Research at Sooth – Anger and Information Processing

Sooth is a social-psychologist founded company that develops community around the art of giving and receiving good advice. Their IOS platform app brings users together for anonymous advice-asking and advice-providing. Despite anonymity, and due in part to the educational materials provided to users, advice tends to be very high quality. I encourage you all to check it out!

For my own contribution, see:

I briefly describe literature studying the effects of anger on information processing, and propose a response to anger that facilitates perspective-taking.

Applying Psychological Research at Sooth: Advice-Giving

Sooth is a social-psychologist founded company that develops community around the art of giving and receiving good advice. Their IOS platform app brings users together for anonymous advice-asking and advice-providing. Despite anonymity, and due in part to the educational materials provided to users, advice tends to be very high quality. I encourage you all to check it out!

For my own contribution, see:

I describe obstacles to giving good advice – including confirmation bias, the illusion of explanatory depth, and passive dehumanization. I then recommend some research and experience-supported antidotes.