Zombies and the Selfish Gene

            With Halloween fast approaching I thought I’d do something that was seasonally appropriate for this blog: Zombies! Well, specifically zombies and selfish gene theory.

            Zombies are currently in vogue. TV shows (e.g., Walking Dead), movies (e.g., Zombieland), and video games (e.g., Left for Dead) have shown that zombies are currently experiencing a Renaissance of popularity in the science fiction (SF) genre. SF is an interesting gauge of public concerns, especially SF of a distopian nature. Whether by intention or accident, such SF resonates with the public’s current fears. Invasion of the Body Snatchers (1956), depicting a situation where townsfolk were being systematically replaced by emotionless, conforming “pod people,” was viewed by many as representing the insidious creeping threat of communist ideals indoctrinating the average American. In the same way, zombie fiction reflects current worries. Early films, such as White Zombie (1932), or even later work like Hammer Horror Films’ The Plague of the Zombies (1966), focused on the mystical cause of zombification, typically linked to voodoo rituals or the like. However, post-millennial zombie fiction, for example, 28 Days Later (2002), The Zombie Survival Guide (2003), and Pride and Prejudice and Zombies (2009), have shifted to a biological, generally viral, vector for zombification.

Zombie art by Paul La Rue, author of the webcomic Exiles

            Once infected through an exchange of bodily fluids the “zombie phage” takes control of the human host, hijacking the behavioural control, and forcing the new zombie to seek out additional bodies to parasitize. The possible self-destruction of the zombie in the process of infecting others is of little concern to the controlling virus: all that matters is the selfish propagating of the virus into new bodies.

            Interestingly, the fictional zombie virus controlling the behaviours of a human host bears distinct similarities to an important concept in evolutionary psychology named the Selfish Gene Theory. In 1976 Richard Dawkins proposed that many aspects of human behaviour could be better understood if one hypothesized that the gene and not the individual person is the actual “unit” that evolutionary selection acts on. The ultimate goal, according to evolutionary theory, is for organisms to pass their genes on to the next generation. Naturally, as resources are finite this leads to behavioural competition between individuals to be reproductively successful.

            Dawkins took this a step further, arguing that the competition exists at the level of the genes themselves, instead of the level of the organism. He proposed that genes are “replicators” inhabiting a host “vehicle.” Replicator genes, barring mutation, copy themselves faithfully across generations. For all intents-and-purposes they are immortal. For example, the same gene that evolved to regulate the development of the dorsal and sides of worms millions of years ago is present in modern humans, fulfilling essentially the same role during our embryonic development. The vehicles inhabited by immortal genes are, however, ephemeral. Moreover, their short-lived bodies are, according to Selfish Gene Theory, expendable. The ultimate destruction of a zombie “vehicle” by shotgun blasts in a movie is acceptable to the viral “replicator” as long as the virus is passed to a new host before the original’s loss. In Dawkin’s view the aim of genes is to selfishly pass themselves to a new generation, thereby maintaining their immortal existence. As a consequence, genes will specifically drive their vehicle to perform behaviours, sometimes highly risky or dangerous ones, provided that such behaviours increase the chance of passing copies of the genes to the next generation. If the host vehicle’s efforts to propagate the genes results in its early destruction, so be it; vehicles are expendable.

            Dawkins’ Selfish Gene interpretation actually helps explain a variety of human behaviours. While such traits as altruism can be explained through this theory, given that I’m contextualizing my discussion with zombies, I’m going to take a less noble (although equally sacrificial) example. Consider that humans (generally males) will not uncommonly engage in high-risk sports (e.g., free climbing, base jumping, street racing, etc.). Competing in such activities may serve to demonstrate their physical fitness, one trait utilized by women in selecting males for mates. The cognitive understanding of the dangers involved in these activities, which may result in short- or long-term injuries or even death, is not as much of a deterrent to the behaviour as one might suspect. If the individual is the evolutionary level of selection, behaviours that lead to the early destruction of said individual should have been evolutionarily selected against long ago. But if Selfish Gene Theory is correct and it is the replicator genes that are in control of the expendable vehicle then the maintenance of such behaviours makes more sense.

            But isn’t it a bit of a stretch to suggest that our genes may be trying to kill us in the aim of reproducing? Well, besides fictional zombies there are real-life examples of parasites hijacking the nervous systems of host organisms, forcing their hosts to suicidal actions that only benefit the propagation of the parasite’s genes. For example, grasshoppers normally avoid jumping into ponds due to the risk of being trapped by the water’s surface tension and drowning. However, grasshoppers infected by horsehair worms are compulsively attracted to water and will hurl themselves into ponds. Once in the water the horsehair worm bursts out of its insect host to find other worms in the pond to mate with, thereby continuing its life cycle. (For more examples of parasites taking control of hosts nervous systems, please see Sapolsky, 2003).

            Lest you’re now feeling totally freaked out that tiny parasitic genes are whispering self-destructive commands to you, do keep in mind that Dawkins only viewed the idea of “conscious” genes actively controlling your every behaviour as a metaphor. Genes are just molecular sequences of codons on your DNA that, ultimately, code for protein synthesis. Genes aren’t intelligent, scheming, manipulators of your actions selfishly sacrificing your ephemeral existence for their own immortality. That being said, the Selfish Gene Theory does provide psychologists with some important insights into real-world “zombie-like” self-destructive behaviour often seen in people.

            Happy Halloween!

References

Dawkins, R. (1976). The selfish gene. New York City: Oxford University Press.

Sapolsky, R. (2003). Bugs in the brain. Scientific American, 288(3), 94-97.

Token Economies

            Given the amount of reading and writing that I do today, it may come as something of a surprise to know that I couldn’t read until I was in grade 3. My parents read brilliantly exciting and interesting books to me that made “See Dick run, run Dick, run,” pale by comparison. I simply memorized whatever the teacher read out loud and parroted it back; it wasn’t until part way through grade 2 that anyone noticed that I wasn’t actually reading. Frankly, I was uninterested and couldn’t be bothered. This all changed for me in grade 3 when my teacher put a world map (with each ocean and sea clearly marked) on the wall and said we were starting a new reading game. Each student in the class got to cut out and colour a medieval-style sailing ship. For every book I read and wrote a one-page book report on, my ship would move one ocean “space” around the world. When my ship circumnavigated the world, I would be rewarded with the materials to make a felt mouse bookmark with googly eyes. This was a revelation for me. I get to read what I want? And a prize for doing it? Sweet! I think my ship circumnavigated the world two-and-a-half times that year; I haven’t stopped reading since. Although I didn’t know it at the time, my reading behaviour had been successfully modified by what behavioural psychologists call a token economy.

            Token economies were popularized in the mid twentieth century in clinical and therapeutic settings, but they were actually used in educational settings at least as early as 1859 (Rodriguez, Montesinos, & Preciado, 2005), and are still used for this purpose today. For example, Breyer & Allen (1975) used one to improve the behaviour of 15 first graders with academic and social behaviour problems that were preventing their progress to grade two; more recently, Boniecki & Moore (2003) successfully applied a token economy to an introductory psychology course to increase student class participation. Besides education and therapy, token economies have also been successfully applied in business and industrial settings.

In their most standard form, token economies provide participants with tokens for appropriate behaviours. These tokens (called “conditioned reinforcers”) can then be traded in for desired back-up reinforcers (a reinforcer is anything that produces a future increase in the behaviour that led to it). In and of themselves, tokens have no actual value. Commonly used tokens are poker chips, points, checkmarks in a record book, and the like. In the case of my grade 3 reading game each new ocean space my ship moved to was a token. Remember, tokens are simply markers indicating that a desired behaviour has been performed. In a clinical application Paul & Lentz (1977), for example, gave tokens to patients in return for maintaining their personal hygiene, attending therapy sessions, keeping their living space clean, and engaging in social interaction. Back-up reinforcers can be anything at all that serves to motivate participants to gain tokens. In my round-the-world reading voyage, the back-up reinforcer was the mouse bookmark. Paul & Lentz offered a more diverse range of back-up reinforcers to their patients, including candy, clothing, cigarettes, additional furniture for patients’ rooms, radio and TV use, and sleeping late; all served to maintain the desired behaviours.

            Token economies are advantageous and effective behaviour modification techniques for a number of reasons. Winkler (1971) showed tokens to be more resistant to satiation than most primary reinforcers (e.g., food or water); a participant might fill up on snacks, and lose motivation, but can’t fill up on tokens. In addition, different people are motivated by different rewards. When working with groups of people it can be difficult for a psychologist to find a single effective reinforcer that is easily deliverable and preferred by all. But because tokens are cashed in for back-up reinforcers, by making a range of back-up reinforcers available each individuals can find something that is personally motivating to work for. Similarly, an individual’s preference for an item may shift over time. Again, by having a range of back-up reinforcers available, if a participant gets tired of receiving one type of reinforcer they can select another to trade their tokens in for. Consequently, token systems often develop behaviours at a higher level than other conditioned reinforcers, such as praise, approval, or feedback (Kazdin 1989). Unlike some reinforcers that must be delivered in an all-or-none manner (for example, consider rewarding a child for cleaning her room by taking her to a movie), tokens can be delivered in a gradual, incremental manner. Instead of one  behaviour for one big reward, multiple behaviours, each receiving a reinforcing token, can be required until eventually enough tokens are gained to get the big reward. For example, a child may receive one token for each instance of cleaning her room, brushing her teeth, putting her clothes away, etc. and ten tokens are needed to be taken to a movie. Generally speaking, the more individual behaviours that are reinforced, the stronger the learning. Finally, the task requirements to receive tokens can be gradually increased and new back-up reinforcers of greater value can be introduced as the program progresses. By starting requirements for token delivery at low levels participants rapidly receive reinforcement and are engaged by the program. However, once established, the costs can be increased until the ultimately desired levels of behavioural performance are reached; the introduction of novel and higher-value back-up reinforcers can help ameliorate negative consequences of increased behavioural cost for token delivery.

            There are, however, some potential issues in applying token economies. Except for things like money or grades, tokens aren’t generally available in real-world settings, so the token-modified behaviour may not persist after the token economy is ended. In business or industrial contexts, this isn’t really an issue as the token economy is pretty specific to the work-place setting, but it may be a consideration in clinical or educational settings if one is trying to modify behaviours that will persist in the outside environment. In addition, it may be possible for individuals to gain tokens in unauthorized ways, perhaps by stealing them or trading them with others in the program, however, this is easily solved by making tokens unique to each individual. Finally, as Kazdin (1989) points out, back-up reinforcers that are extraneous to the setting may be difficult to remove after the token economy has been completed (e.g. using tokens to purchase food reinforcers in a classroom may be problematic as food is usually not allowed in classroom settings). Of course, by initially selecting setting-appropriate back-up reinforcers this problem can be avoided.

            Finally, let’s examine a classic example of a token economy that ran for over a decade in the industrial setting of two uranium mines (Fox, Hopkins, & Anger, 1987). Tokens were given to miners for three things. First, not having accidents or injuries for specific periods of time; this provided impetus for individual miners to be more careful. Second, no miners in an entire work group being injured for a period of one month; this motivated miners to look not only to their own safety, but also that of their co-workers. Third, suggesting safety improvements that were implemented at the mines. Tokens could be exchanged by miners and their families at local redemption stores supplied with hundreds of items of merchandise; additional items were available via mail-order.

            So, did it work? The graphs below show the number of days lost due to accident and injury. Compare the data from the baseline periods, before the token economy was adopted to the data after implementation. Both mines show a clear benefit.

Similarly, the token economy resulted in a substantial reduction in time lost to injuries after the token economy was put in place, as shown in the next set of graphs.

Of course, from a business perspective, ultimately one has to ask whether or not the token economy actually led to a financial benefit. A quick look at the graphs below demonstrates the dramatic reduction in costs to the mining company due to accidents and injuries. Reduced costs equals higher profits.

            The applications of token economies are practically endless: personal fitness programs, retail sales, return of library materials, and dieting can all make use of token economies to motivate behavioural change.

Have you either implemented or taken part in a token economy, or know of someone who has? Feel free to add a comment to tell me about it.

References

Boniecki, K. A. & Moore, S. (2003). Breaking the silence: Using a token economy to reinforce classroom participation. Teaching and Psychology, 30(3), 224-227.

Fox, D.K, Hopkins, B. L., & Anger, W. K. (1987). The long-term effects of a token economy on safety performance in open-pit mining. Journal of Applied Behavior Analysis, 20(3), 215-224.

Kazdin, A. E. (1989). Behavior modification in applied settings (4^th ed.). Pacific Grove, CA: Brooks/Cole.

Paul, G. L., & Lentz, R. J. (1977). Psychosocial treatment of chronic mental patients: Milieu versus social learning program. Cambridge, MA: Harvard University Press.

Rodriguez, J. O., Montesinos, L., & Preciado, J. (2005). A 19th century predecessor of the token economy. Journal of Applied Behavior Analysis, 38, 427.

Winkler, R. C. (1971). The relevance of economic theory and technology of token-reinforcement systems. Behaviour Research and Therapy, 9, 81-88.

Measures of Managerial Success and Evolutionary Psychology

A research study by Jane Sturges (1999) found that male and female business managers measure success by very different metrics. Sturges interviewed 18 female and 16 male managers in a leading UK telecommunications company with the aim of answering two questions:

            1. What do managers conceive career success to be for themselves? and

2. Do female managers have different ideas about what career success is for them than male managers do?

Based on the interviews, managers were categorized as belonging to one of four types of business-orientation categories.

1. Climbers, who defined career success largely in terms of their position in the business hierarchy and their progression through promotions and increases in pay grade.

2. Experts, who measured career success as achieving a high degree of competency at their job and being recognized personally as good at what they did. For Experts, the content of their job was more important than their hierarchical position in the organization.

3. Self-Realizers, who determine success by the idea of achievement at a highly personal level; personal enjoyment in the job and maintaining a balance between their home and work life was a common measure of success for this group.

4. Influencers, who defined success as being able to do things at work that had tangible and positive outcomes for the organization they worked for, regardless of their position in the organization’s hierarchy.

Here’s the breakdown of where the male and female managers fell on the business-orientation categories:

What’s so interesting about this is that three of the four business-orientation categories are dominated by one sex. Additionally, while most of the men, regardless of categorization, defined success by the position they attained in the organization’s hierarchy. None of the women defined success strictly by hierarchical advancement, and those that did indicate it was a component of success saw hierarchical achievement as a means to some other end. Clearly, there’s a big difference in how male and female managers define personal success.

            Sturges adopted a fairly traditional socio-cultural driven interpretation for her findings, suggesting that, “…managers’ ideas about career success reflect the social context in which they develop as adults” (p. 250). That is, specific societal-driven learning shapes managers’ idealizations of business success. Sturges added that the “…effects of socialization on women managers’ conceptions of career success are likely to be reinforced by their experiences as women in what is still a male-dominated profession” (p. 250). Given this, she hypothesized that if women have learned that the gender imbalance in business means that advancement to the highest managerial levels “…is not readily available to them, then they might choose to refocus their ideas of what success is on other less tangible and more internal criteria, which they believe to be more easily attainable” (p. 250).

            While learning via socialization is certainly a possible interpretation of the results, the field of Evolutionary Psychology offers an alternative perspective. Evolutionary psychologists utilize Darwinian evolutionary theory to predict and explain human behaviour patterns. In brief, Evolutionary Psychology assumes that natural and sexual selection pressures in the past produced behaviours that conferred advantages on our ancestors, and that these genetically influenced behaviours are still with us in our modern environment.

            So, what sorts of behaviours were selected for in ancestral males and females? According to Evolutionary Psychology, there were some profound differences between the sexes. Because reproductive costs are high for females (gestation, nursing, and childrearing are very energetically expensive), ancestral females looked for male mates who could provide resources to sustain themselves and their offspring. In addition, they became very good at social interaction. Women able to form strong social alliances gained advantages with respect to shared childrearing, reciprocal food and information exchange, and emotional support; empathy was a strongly selected trait in women. In contrast, competition for social status, territory, and resources was selected in males. Males did form social alliances, but these were generally narrowly focused on the tasks of hunting, warfare, or intra-group politics. In the end, those males lacking in resources were less likely to attract mates, making them evolutionary dead ends.

            Fast forward to the modern corporate environment. Sturges’ findings fit well with Evolutionary Psychology theory. Males, evolved to compete for prestige, social status, and resources comprise all of the Climbers. Evolutionarily successful women were those who could simultaneously manage childrearing and survival tasks; this fits well with Self-Realizers’ needs to balance home and work life. Six of the seven Self-Realizers were women. Because women were not spending their time competing for tribal dominance and leadership, and because of their social support networks, individual women were able to become “specialists” in various “industrial” and social roles (e.g., midwifery, clothing manufacturing, herbalism, shelter maintenance, matchmaking, etc.). Seven of the nine Experts were women. What about the fairly even split between the sexes in the Influencers category? We humans are a highly social species that naturally organize into groups. If individuals contribute to the collective good of the group, such that the entire group is stronger, this has a direct personal benefit for the individuals whose influence brought about this positive outcome. In the past, both sexes experienced evolutionary pressures to influence tribal systems; the same predispositions are still seen in the modern organizations.

            It is important to note that Evolutionary Psychology does not discount socialization. Classic studies by Albert Bandura (1977), for example, on observational learning demonstrate the significance of social reinforcement on human behaviour. That said, as further research highlights the differences between men and women in the business sector (e.g., see Ruderman & Ohlott, 2005 for sex differences in information processing, stress responses, and motivation), a greater appreciation and understanding that these distinctions may be due to evolutionarily selected genetic predispositions is warranted. While genetic predispositions can be altered via learning, unique techniques need to be developed to take into account the evolved underlying differences in female and male psychology to make programs in executive coaching, leadership development, and human resources more successful and productive (e.g., see Hopkins, O’Neil, Passarelli, & Bilimoria, 2008). Further, by accepting evolved differences in male and female managers, organizations could benefit by recognizing and utilizing each sex’s adaptations to their advantage. Don’t fight evolutionary predispositions, but work with them for greater business success.

            My next blog will move back to a more traditional behavioural modification topic, token economies, and their application to business and education. See you in a week!

References

Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice Hall.

Hopkins, M.M., O’Neil, D. A., Passarelli, A., & Bilimoria, D. (2008). Women’s leadership development strategic practices for women and organizations. Consulting Psychology Journal: Practice and Research, 60(4), 348-365.

Ruderman, M. N., & Ohlott, P. J. (2005). Leading roles: What coaches of women need to know. Leadership in Action, 25, 3-9.

Sturges, J. (1999). What it means to succeed: Personal conceptions of career success held by male and female managers at different ages. British Journal of Management, 10, 239-252.