Effective or ineffective leadership in apocalyptic situations

As a professor of management, I infrequently get to discuss zombies in class. The topic rarely arises and though zombies have been taken more seriously in the last decade as a mainstream horror element. But a recent re-watch of Criterion’s excellent re-mastering of Night of the Living Dead, I thought a modern Organizational Behavioral perspective might be interesting to take in discussing the actions (and inactions) taken in that film. For those who have not seen it, it isn’t nearly as gratuitous as you may think though the subject matter deals with topics still taboo and one or two scenes I still find unsettling. There will be plentiful spoilers below but the film is available widely for free (check archive.org) or the above mentioned Criterion release is a great option.

The film opens with two sets of dyads. Barbara and her brother (Johnny a know-it-all unsentimental jerk) are together and later Barbara finds herself in a large house with Ben (a fellow survivor who is scrappy and full of ingenuity). Though Barbara begins the film as reasonably relatable and quick-thinking, she is so deeply unsettled by the first 10 minutes to be wallpaper for a large chunk of the film. This is regrettable from a modern perspective where we would hope that individuals would have the internal fortitude to rationally recognize their situation and respond with action as opposed to shutting down. Harry, loud-mouthed though castigated coward, has a very similar reaction, hoping to put his head down (in the cellar) and wait for things to end. Barbara is waiting and witless due to shock (which she eventually comes to terms with) but Harry is just as wonton as Barbara through his actions. There are other characters (the young lovers Judy/Tom) and Harry’s longsuffering wife Helen who receives an unnecessarily violent end at the hands of her daughter (Karen) but they will factor less into this essay.

Ben quickly asserts himself as the leader of the group after the other players arrive. This was notable at the time as Ben is African American, though this is only subtly commented on by the other characters. Harry appears unwilling to take or accept orders but it is not made explicit that this is due to Ben’s ethnicity or some other characteristics. Ben takes command and begins making orders. Ben is a task-focused leader, primarily focused on distributing work to other individuals within the small collective of survivors. “Find me some nails, the longer the better” he tells Barbara, which is the only task she accomplishes before falling into a fit. Later in the film, Harry criticizes Ben’s work on boarding up the house, attempting to assert his opinions on the value of returning to the basement as the most reasonable option. Some commentators note that a retreat to the basement ends up being what saves Ben at the end of the film, but I agree that staying in the basement was not a good plan in general.

So, now to the question at hand. Is Ben a good leader? I think it is important to consider that our characters have limited information about the world. So success or failure are not entirely determined based on their actions. Reasonable actions could lead to failure when given incomplete or inaccurate information. The survivors are unaware that there are teams within their area working to secure the countryside of the dead. They are explicitly told that they should seek out the rescue centers and not wait for help. They chose to trust the newscasters and this led them down a risky set of activities. If they had instead waited for the sheriff’s posse on the first floor of the house, they would have been able to alert the posse of their state as survivors before they were in as much danger. The slow, careful emergence from the basement as Ben made at the end of the film would have surely meant death for some if not all of them if they had agreed with Harry’s plan.

So, Ben and several of the others decide that no help is coming but that help is available nearby. They construct a plan based around the need for transportation, and enact it. Several issues arise in Ben’s decisions at this point. Tom states that he is familiar with the truck though he still struggles to get it started. Ben’s assertion that he is unfamiliar with it strikes a wrong note as he had driven it at least a few miles to get to the farmhouse. Judy, at the last minute decides to come along. This addition to the team wouldn’t have necessarily caused a problem, but the unplanned nature led to a more hurried escape then they may have otherwise experienced. Ben over-reacts to this hurried nature, firing at the locking mechanism on the gas pump, leading to a leak that inevitably catches the truck on fire, due to Ben’s careless placement of the torch. These issues, though inadvertent and based on Ben’s situational awareness, led to a much worse situation for the group.

Was Ben a good leader? Ben identified an issue, built support for it, and enacted a plan. Ben, however, did not seek or receive group consensus on the actions. The women in the film are not given their own agency (a film can only I have so many progressive elements I suppose) and thus their reactions to their own circumstances are, in part, treated as independent of the influence of the male protagonists. The women accept orders but are not necessarily happy about it or share their own thoughts fully (except for Helen though she serves as Karen’s nurse for much of the film and is therefore out of consideration). A better leader might have tried to determine what other’s thoughts were about his plans. Instead, Ben is strong and firm, but ultimately leads an unsuccessful attempt to fuel the truck. As I mentioned earlier, the premise of the mission was less necessary than the survivors thought (rescuers appear the next morning) but I can’t help but think that more careful consideration by Ben could have made all the difference.

It is hard to tell how we will each react in stressful circumstances, many of which we experience are not nearly as dangerous as those faced by the protagonists in Night of the Living Dead. But, creating a positive leadership mentality of consideration and analysis can help encourage us to default toward better decision making practices in general, especially in high stress situations. Taking some time to think through whether or not all opinions are heard in an everyday circumstance takes thought but is easy. Taking that same action in a high stress environment may be tougher, but is just as valuable if there is time to consider multiple options.

 

Learning to do a meta-analysis

My last post about what a meta-analysis is, was partially because I decided to learn how to do a meta-analysis. I decided that while I was walking home last Friday and I realized I could have more than one blog. I quickly came up with a fantastic name for a new blog that had something to do with meta-analyses and then promptly forgot about it. I don't know if I'll start a whole new blog to discuss my process of learning about and/or carrying out a meta-analysis but I figured I would start blogging here.

I have a tendency to want to learn about new statistical techniques without then using them to do anything. I think I have to agree that actually using (or thinking about using) a new technique is much more useful in the end. Kind of like you may not think that doing example problems will help you understand a concept but (at least when going through some of the meta-analysis material I've been looking at) it can be really helpful. I have decided that the question I am going to plan / actually pursue is transactive memory's role on performance and turnover's role as a moderator. Not only is this an area I am interested in so I have a lot of understanding already, but there are not any meta-analyses I know of looking at this topic. DeChurch and Mesmer-Magnus did a meta-analysis in 2010 about team cognition which encompassed TMS but I think that a more narrow approach may be enlightening.

I am basing my current exploration on of the article I mentioned in my last post "How to do a meta-analysis". The accompanying website for the article is not super easy to find but is here: resource page. The first author's website, Discovering Statistics (aka Statistics Hell) seems to have a lot of good resources as well. The researchers who wrote the article, also wrote several scripts that can be used in SPSS and R (two statistical packages, the second is free). The webpage doesn't describe the process of preparing the data (you'll want to read the paper or this short article for that) but it does provide some example data for you already. The authors claim this data is (or is based on) published articles, so I'm guessing that I should be able to replicate the work those researchers did.

If I continue this exploration further, I'll keep you all in the loop.

What is a meta-analysis?

Many of you may have heard the term meta-analysis either in this blog or other places on the web. Because of the amount of data and the power of our analysis software, these kinds of analyses are done fairly frequently in a lot of topics. So what is a meta-analysis? Essentially, it is a statistical way of adding a bunch of different studies together that are looking at the same thing to determine what the real effects are. Let me use an example.

If you are looking at 2 studies (or 2 articles reporting on studies) that are looking at the same question but come to different results, what can you use to determine which is the most valid? There are a few general rules of thumb. If one of them comes from a more notable research institution, it may be better because these schools typically have stricter institutional controls. Another important factor is sample size and population. If the sample is entirely college students, there are reasons why you might not trust that finding as much as if the sample was more diverse. Also, if one study had 50 people and the other had 500, then you might trust the larger one more.

It may seem obvious, but why actually do we trust the more diverse or the larger studies? Studies where they find effects even with diverse samples suggests that the effect is likely to be more prevalent. Diversity always adds some amount of variation to human subjects research. In a study I am running, we are using computers and we found that it was a good idea to limit the age of participants because some participants had much more trouble since they were not as familiar with computers as the younger participants. So, reducing the diversity of the sample can let researchers narrow in on results they are interested in. Sample size effects the likelihood of finding an effect to begin with. As the sample size increases, a number called the standard error decreases in the analyses. This means that the analyses can become more confident of the effects each variable has.

What a meta-analysis is, is a tool that lets researchers combine multiple studies together. Through that process, the sample size gets bigger which allows us to be more confident and, due to the aggregation process, the sample also becomes more diverse because studies will have used different kinds of people and possibly different methods in carrying out the experiment. Meta-analyses can be done incorrectly and can be misleading, but a good rule of thumb would be to trust a meta-analysis about a topic more than any single study.

Extra Fun Facts: File-Drawer Effect

The process of doing a meta-analysis of course adds some difficulties for the researcher in trying to 'wash out' the potential added noise (a term for unintended variance) from the analysis. There are many possible problems such as the 'file-drawer effect'. It is well-known that a lot of the work that scientists do never gets published. A big factor of this is non-significant effects. If you run an experiment, for example, and do not find what you are looking for, you may assume that you did something wrong. One professor I had mentioned that he ran one study over 3 times, never quite finding the effects he was interested in. Because of this, he never published any of the studies. [Later on he did a small meta-analysis of just these experiments and found that there was a small effect that he was only able to see when adding all of the data he had collected together.]

There are two main reasons for the file-drawer effect. Researchers may be embarrassed or not see value in proclaiming to the world that they found nothing (significant effects are 8 times more likely to be submitted), and academic journals are hesitant to publish articles without significant effects for the primary variables of interest (7 times less likely to be published). There are some legitimate reasons for this hesitancy. A study can fail to find effects for a lot of different reasons (actually no effect, poor design, too small sample size, inappropriate analysis, etc.), but there are fewer conditions under which a study will find effects when there are none. Therefore, if you did a meta-analysis only using the data that were published, there may be an over-representation of the actual effect than in reality. If you are trying to determine the average grade for the class but only included students that made above a certain grade or attended every class session, you will get an average that is likely to be different from the actual average. There are various and sometimes complex ways that researchers try to deal with these problems but it is always a concern.

* I used Field & Gillett (2010) "How to do a Meta-Analysis" significantly in this post.