Embracing Evolutionary "Cheating"

The most important question of the Hendricks Forum was this: were all researchers CITI certified? If not, did they share this secret with their subjects? Does the scientists have secret brainscans showing which “terror modules” light up when he informed his participants-slash-victims of his wildly unethical research methodologies? We may never know.

What we can know, however, is how Alford & Hibbing’s findings can be immediately applied to the classroom. Consider a common learning situation: two students are studying for a graded, non-curved assignment, and one student is in a position to help another. Many educators have believed that the best way to deter one student from doing work to another is to increase penalties and be on the look-out for side-payments (popularity granted to a smart but dorky student by popular but dull ones, for instance). However, if people will do more work for another than the other would ask for if the issue of representation is involved, then the range of potential cheaters becomes much broader. No longer are we looking only for those who want to increase their own station, but at altruists who are completing educational “puzzles” for another student.


We can contrast the academic cheating behavior of the “economic man” and the “wary cooperator” in a simple experiment. Use a subject and a confederate, and inform them that because of a last-minute conflict, the University has asked them to take their skill tests unsupervised in the same room at the same time. Full credit will go to right answers, and no credit will go to wrong answers. Make it possible for a student to help another cheat, but after the end of the run inform him that he may accuse the other of cheating. Add a point to the cheater’s score, but inform the subject that the accusation will zero out the confederate’s There are four conditions with four possible responses to test whether students faced with the dilemma of helping another cheat will act like wary cooperators or rational actors:

The conditions:

  • Condition I. Introduce Subjects. Confederate suffering.
  • Condition II. Introduce Subjects. Confederate offers bribe.
  • Condition III. Don’t introduce Subjects. Confederate suffering.
  • Condition IV. Don’t introduce Subjects. Confederate offers bribe.

The responses:

  • Response A. Subject Assists. Subject keeps silent.
  • Response B. Subject Assists. Subject informs on confederate.
  • Response C. Subject Doesn’t Assist. Subject keeps silent.
  • Response D. Subject doesn’t Assist. Subject informs on confederate.

Standard economic theory gives the following predicted paths

  • If Condition I, should choose Response D, least likely to favor Response A
  • If Condition II,should choose Response B, least likely to choose Response C
  • If Condition III, should choose Response D, least likely to favor Response A
  • If Condition IV, should choose Response B, least likely to follow Response C

Classroom teachers, of course, view “D” as the only acceptable path.

Because of the conflicting possible frames this situation could be put in, I do not believe we can yet create a “genetic factors” model with this same degree of precision. However, we can identify where it flatly disagrees with the economic model of cheating.

Under Condition I, D should be the least likely outcome. Under introduction, the subject should be prepared to help the confederate with no personal compensation. Likewise, free-riding against an innocent but suffering player is doubtful. Likewise, under Condition III D should also be the least likely outcome. (Two variations are not shown in this mini-experimental design: confederate suffers and offers bribe and confederate doesn’t suffer and doesn’t offer bribe. The first possibility confounds fault and no-fault non-cooperation, while the second should have zero “cheating” under both models. However, that doesn’t mean it’s entirely useless – it may be worthwhile, for instance, to see if the subject would retaliate if his requests for assistance from the confederate is rebuffed by accusing the confederate of cheating, even if we make the reward for turning in a cheater negative!).

A finding that confirms wary cooperation would have profound impact in how we deal with cheaters. If we find that the most pro-social students cheat out of empathy, this further throws the value of individual work into doubt. Instead, work should be group-oriented as much as possible, because this will exploit the student’s natural desire to help a peer in need while demarcating out-group-members as non-peers for the purposes of cooperation.

Development Biology: Even Quicker and Dirtier Than Usual

If you felt that my quick and dirty literature reviews on learning disabled students and ultimatum game were too polished, too coherent, and too well written, this is the post for you! Below the fold are some sloppily thrown together notes, for my benefit only. I’ll try to write an actually readable post later in the day.


Among even the educated public, evolution is a controversial and poorly understood topic (Alter & Nelson, 2002).
Evolutionary psychology is a fruitful research area that generates specific, testable, and interesting hypothes (Buss, 1995).

Except in extreme cases, nature and nurture cannot be seperated (Vetta & Courgeau, 2003). Additionally, new abilities emerge in predictable ways (Carpenter, et al. 1998). “Developmental biology” — a synthesis of information-processing theory and evolutionary psychology — may be the next step in understanding cognitive development (Bjorklund, 1997). Simulations have been used to model information processing theory in childhood art (Burton, 1997).

Humans have inborn, social affections (Hofer, 1987) and physical abilities (Thelen, Ulrich, & Wolff, 1991).Group selection may explain cultural change in as little as five to ten cutires (Soltis, Boyd & Richerson, 1995)..
The view that altruism may be truly altruistic, rather than an expression of genetic or individual selfishness, is gaining ground (Piliavin & Charng, 1990).

Neurobiology and evolutionary biology emerged at around the same time, the 1960s and 1970s (Sokal, 1970).

The issue of group and individual selection is widely debated in adaptionist circles, but group selection theories are more favored in genetic circles (Goodnight & Stevens, 1997).

Six broad categories of genetic-environmental questions exist: the degree to which it affects quantitative variations, the degree to which it influences social structure, the how human populations face selection pressures (Thoday, et al, 1970).

r means growth rate, while K refers to the saturdation density (Kurihara, Shikano, & Toda, 1990).
Interpersonal skills may fall into basic interaction, communication skills, conflict resolution, and team building (De Natale & Russell, 1995).

The origin of multiple intelligiences has been studied by examining the traces of human ancestor and competitor species (Wunn, 2000). Indeed, evidence argues that most of the domains that Gardner originally outlined are actually collections of domains (Visser, Ashton, & Vernon, 2006a; 2006b). A view of modular intelligence that is effected by genetic-environmental interaction has been used to fight racist notions through scholarly literature (Graves & Johnson, 1995). Kinesthetic intelligence may split into fine motor intelligence and whole body intelligence (Gardner, 2006).

Alter, B.J. & Nelson, C.E. (2002). Perspective: Teaching Evolution in Higher Education. Evolution 56(10): 1891-1901.
Bjorklund, D.F. (1997). In Search of a Metatheory for Cognitive Development (Or, Piaget Is Dead and I Don’t Feel So Good Myself). Child Development 68(1): 144-148.
Burton, E. (1997). Artificial Innocence: Interactions between the Study of Children’s Drawing and Artificial Intelligence. Leonardo 30(4): 301-309.
Buss, D.M. (1995). Evolutionary Psychology: A New Paradigm for Psychological Science. Psychological Inquiry 6(1): 1-30.
Carpenter, Malinda, et al. (1998). Social Cognition, Joint Attention, and Communicative Competence from 9 to 15 Months of Age. Monographs of the Society for Research in Child Development 63(4).
Di Datale, J. J. & Russell, G.S. (1995). Cooperative Learning for Better Performance. Music Educators Journal 82(2): 26-28.
Gardner, H. On failing to grasp the core of MI theory: A response to Visser et al. Intelligence 34(5): 503-505.
Goodnight, C.J. & Stevens, L. (1997). Experimental Studies of Group Selection: What Do They Tell Us About Group Selection in Nature?. The American Naturalist 150: S59-S79.
Graves, J.L., Jr., & Johnson, A. (1995). The Pseudoscience of Psychometry and The Bell Curve. The Journal of Negro Education 64(3): 277-294.
Hofer, M.A. (1987). . Early Social Relationships: A Psychobiologist’s View. Child Development 58(#): 633-647.
Kurihara, Y., Shikano, S., & Toda, M. (1990). Trade-Off between Interspecific Competitive Ability and Growth Rate in Bacteria. Ecolony 71(2): 645-650.
Pilviavin, J.A. & Charng, H. Altruism: A Review of Recent Theory and Research. Annual Review of Sociology 16: 27-65.
Sokal, R.R. (1970). Another New Biology. BioScience 20(3): 152-159.
Soltis, J., Boyd, R., & Richerson, P.J. (1995). Can Group-Functional Behaviors Evolve by Culturla Group Selection: An Empirical Test. Current Anthropology 36(3): 473-494.
Thelen, E., Ulrich, B.D., & Wolff, P.H. (1991). Hidden Skills: A Dynamic Systems Analysis of Treadmill Stepping during the First Year. Monographs of the Society for Research in Child Development 56(1).
Thoday, J.M. (1970). The Interrelation between Genetics and the Social Sciences. Population Studies 24: 49-54.
Wunn, Ina. (2000). Beginning of Religion. Numen 47(4): 417-452.
Vetta, A. & Courgeau, D. (2003). Demographic Behaviour and Behaviour Genetics. Population (English Edition, 2002-) 55(4/5): 401-428.
Visser, B.A., Ashton, M.C., & Vernon, P.A. (2006a). Beyond g: Putting multiple intelligences theory to the test. Intelligence 34(5): 487-502.
Visser, B.A., Ashton, M.C., & Vernon, P.A. (2006b). g and the measurement of Multiple Intelligences: A response to Gardner. Intelligence 34(5): 507-510.