Steven C. Hayes. Variation and Selection in Rules and Rule-Governance: The Perspective of Behavioral Psychotherapy

By Peter Turchin April 6, 2012 No Comments

The Latin root of “rules” (regula) originally just meant a straight stick, and later a stick used for measuring. That sense remains in English (e.g., a wooden ruler), but a later sense was simply that of any consistent pattern (e.g., ruled paper, or “I don’t eat before noon, as a rule”). The most recent sense of the term etymologically speaking is “to govern.” A “rule” in that last sense is a verbal statement (or a person who makes them – a “ruler”) intended to produce some behavioral regularity.

Ostrom limits the term “rule” in this article to the final sense, which is helpful because it avoids confusing verbal rules that are derived by scientists merely from the observations of behavioral consistencies, with the verbal specification of contingencies (contexts, actions, and consequences) so as to regulate human behavior. The ultimate question in the target article is how such rules evolve. In her hands, rules are cultural genotypes – a powerful and apt metaphorical extension of genetic evolution.

Evolution of Rule-Governance

As a psychotherapist and language researcher, in my comments I want to point several steps that behavioral and cognitive practitioners have learned can be helpful at the psychological level in altering rules and rule control. As Wilson and Gowdy (in press) point out, in the same way that disruption of gene flow leads to increases in speciation, disruption of communication between islands in the academic archipelago can lead to divergence so great that intellectual cooperation is impossible. The academic island I live on is a historically isolated one — behavioral psychology. Evolution science is a kind of “water taxi” to other academic islands, but I hope I can be forgiven for presenting some background first so that part of my “island culture” can be in this conversation.

B. F. Skinner long ago distinguished contingency shaped behavior from rule-governed behavior (1966) and although his specific analysis failed, scholars in his contextual behavioral tradition have continued to work on the mechanisms, development, phylogeny, and function of verbal rules. Rules involve the verbal framing of contingencies (a modern tweak of Skinner’s definition, 1966, p. 243), but “verbal” needs to be defined. Tinbergen’s “four questions” (1963) provide a structure for considering the issue.

Mechanisms or Processes. Verbal humans derive relations even among arbitrary events, mutually and in combination, and stimulus functions change as a result (Hayes et al., 2001). Humans without this ability do not develop normal language (e.g., Devany et al., 1986).  The core phenomenon was shown with the discovery of “stimulus equivalence” (Sidman, 1971), but it has expanded over the years to include many other types of verbal relations, such as difference, opposition, comparison, and the deictic relations (e.g., I-You, Here-There, Now-Then) that are central to perspective taking (Berens & Hayes, 2007; Weil & Hayes, 2011; Steele & Hayes, 1988).

As a practical example of this skill, consider comparative relations. Very young children who know that coins can be used to buy candy will prefer a quarter over a nickel over a dime based on the non-arbitrary relation of relative size.  When comparative relations become fully verbal and thus arbitrarily applicable, that same child will prefer a quarter over a dime over a nickel. The actually stimuli used no longer matter –  anything in a variety of comparative network can be reliably related once the core skill is training (e.g., A < B < C, or A < B > C etc., see Berens & Hayes, 2007 for an empirical demonstration with young children).

The derived and arbitrary nature of human verbal relations enormously expands possible variation. If a non-human primate learns eight sign à object relations, only these eight are available. In verbal humans these eight trained relations lead to several thousand derived relations because every sign and relationship between and among the signs can be related one to the other in all directions, and to every object and relationship between and among the objects in all directions (cf., Deacon, 1997). The ability to derive such relations is central to human reasoning and problem solving (Barnes-Holmes et al., 2001).

Development. The capacity to learn arbitrarily applicable relational responses is innate in humans, but it appears to require operant training during the developmental period to take advantage of this capacity (e.g., Lipkens et al., 1993; Luciano et al., 2007; McHugh  & Stewart, 2012). If that is correct, the symbolic inheritance stream in humans (likely at least 100,000 years old, Nichols, 1992) is itself initiated by learning processes that arguably date to the Cambrian period (Ginsberg & Jablonka, 2010). Children learn classes of relational actions such as same, different, or bigger, as response frames (“relational frames”) that can be applied to anything. Events are “verbal” when they have their functions because of these relational frames (Hayes et al., 2001). If rules indeed are genotypes, then relational framing is how “cognitive nucleotides” are assembled into coherent sequences that can produce behavior.

Phylogeny. Although cognition, culture, and cooperation are all characteristic of humans, the phylogeny of relational framing seems more readily understandable if it is assumed that cooperation came first. Such a perspective fits with the centrality of multi-level selection in human evolution (Nowak et al., 2010; Wilson & Wilson, 2007) but moreover it explains how the relational aspect of verbal events might have been immediately advantaged as they evolved in the context of a highly social species.

A non-human species, learning to point to an object when hearing or seeing a characteristic sign, will not thereby know to produce that sign when seeing the object. Language trained chimpanzees fail this task (Dugdale & Lowe, 2000), but human infants do not (Lipkens et al, 1993; Luciano et al., 2007). Non-human speakers and listeners communicate in an interlocking system but “listeners acquire information from signalers who do not, in the human sense, intend to provide it” (Seyfarth & Cheney, 2003, p. 168; see Tomasello, 2008). The reversibility of speaking and listening roles in a single communication system requires the ability to reverse the order between signs and referents, and that is precisely what non-humans do not do, while even 12 month old babies show that ability (Lipkens et al., 1993). For humans, speaking and listening stimulates the same linguistic regions of the brain (Menenti et al., 2011) because learning object à sign, implies sign à object by derivation. Thus, a person teaching a listener [name] à [point to object] can for example later ask the listener across a canyon or around a corner to report and be told what is there based on the relation [see object] à [say name]. The major human transition might have provided the cooperative environmental context for human symbols to operate in this relational way (cf., Nowak & Highfield, 2011; Tomasello et al., 2005; Tomasello, 2009).

Function. Verbal meaning and rules themselves can thus be thought of in a functional sense as acts of social cooperation and communication that afford greater environmental and social control. Clinical researchers in the area of rule governance have distinguished three major functional classes (Hayes, 1989): expanding social influence (called “pliance”); orienting the listener to environmental contingencies (“tracking”); and altering motivation (“augmenting”). Thus, although in the present the functions of verbal reasoning and problem-solving are primarily thought of as instrumental, their primary original roles were likely social (e.g., see Mercier & Spencer, 2011).

Flexibility and Rigidity in Rules and Rule Following

The approach to rules I have described has emerged from clinical behavior analysis and cognitive behavior therapy. Behavioral health problems are called “mental” illness because they involve the domination of unhealthy or unworkable rules over behavior and in that sense clinical practitioners deal with the evolution of rules and rule-governance at the psychological level as an everyday matter. In what follows I will simply list five major findings on that topic that have emerged from this wing of behavioral psychology occasionally adding possible implications for the target article. I realize that many of these observations are already supported by the work of Ostrom and others, but I will not stop to document that fact in this short comment.

 1. When tightly held, rules tend to induce a relative insensitivity to direct consequences of responding outside of those specified in the rule itself (Hayes, 1989). This is a very common clinical situation. Too much focus on what “should” have occurred instead of what did occur, and too much focus on “being right” or following the received wisdom from others as opposed to relying on experience, make it more difficult to move toward chosen goals (cf., Sheldon et al., 2004). These insensitivity effects are especially strong with pliance.

This implies to me that anything that fosters rule-governance as a matter of mere social compliance only, will reduce the ability of rules to change. Clinicians foster choice, personal responsibility, and contact with the short and long impact of rules as part of creating more psychological flexibility.

2. Avoidance based rules are particularly rigid, and difficult to change. A classic example in the clinical domain is experiential avoidance (Hayes et al., 1996). Trying to improve life by avoiding difficult thoughts, feelings, or bodily sensations, even if these are unavoidably part of behavior change processes, arguably accounts for more of the variance in more problem areas than any other psychological approach to change known in clinical science (Chawla & Ostafin, 2007; Hayes et al., 2006). This approach is passed down socially (Cheron et al., 2009; Williams et al., in press), impacting the function not just of individuals but also organizations and groups. We have known for some time, for example, that organizations that are more flexible are more effective (e.g., Seppala, 1989), but we are learning that organizational flexibility cannot be taken advantage of by participants unless they themselves are psychologically flexible, and able to experience a wider range of emotions or thoughts without escaping or avoiding (e.g., Bond & Bunce, 2003; Bond et al., 2008).

This implies to me that cultures and customs that avoid uncomfortable topics, that are weak in perspective taking, and that do not allow expressions of distress to be linked to open processes of conflict resolution, are going to interfere with rule flexibility and change. Conversely, positively focused rules linked to specific and direct experience will be more modifiable.

3. Flexible attention to the now is necessary for the healthy evolution of rules and rule-governance. In clinical situations, contact with the present moment is helpful in providing experiential feedback for behavior, including rule-governance, but especially so if attention can be allocated in a flexible, fluid, and voluntary way (Wells, 2000). Both attentional persistence and change are important.

Extending this to the social level suggests that rules will work best when they are linked to good quality and timely data, but especially so if groups can allocate time and effort to decisions in a flexible, fluid, and voluntary way. If the squeaky wheel always gets the grease, that is a problem. If one data source dominates over all others, that too is a problem.

4. Cognitive flexibility is more important over time, than having the “right rules” at any one point in time.  The ability to step back and consider a variety of rules is clinically predictive of positive behavioral development (e.g., Fresco et al., 2006). There is some evidence that this in turn is fostered by greater mindfulness and emotional flexibility (Palm & Follette, 2010).

This suggests to me that groups that can tolerate ambiguity, and rapidly generate good quality alternative rules without closing down alternatives, will do better over time regardless of starting point.

5. Values and meaning matters. You can only evaluate pragmatic workability with reference to a goal – values provide part of the selection criteria for rules as cultural genotyopes. Practically speaking, people who allow positive values to provide meaning in the moment, view values as a matter of choice, and embrace those values they hold as important, do a better job of persisting or changing in rule-governance as needed (Cohen et al., 2006).

This suggests we need to know what the larger set of values and goals are of a group in order to predict and understand rule adherence and change. Instrumental rules about resource allocation occur in groups that may have other values at stake (e.g., maintenance of community), and some understanding of these would be helpful.

6. Not all behavior is rule-governed. Rules can be ironic or self-contradictory, or wander into territory that is simply poorly governed by rules (e.g., self-contradictory rules such as “be spontaneous” or “don’t think about your fears” are examples, see Wenzlaff  & Wegner, 2000). Much as gene expression is regulated by epigenetic processes, it is important clinically to have processes at hand to regulate the behavioral expression of unhealthy cultural genotypes or “symbotypes” (Wilson et al., under submission). Examples of what we might call episymbolic processes may include the use of humor to deal with embedded racism, psychological acceptance to deal with difficult emotions, or perspective taking or contemplative practice to deal with difficult thoughts (Hayes et al., 2004).

This implies two things to me. First, it seems important to track other streams of evolution and inheritance (behavioral, epigenetic, genetic) when dealing with rules and rule governance. Second, at the social level we should consider social institutions that undermine unhealthy rule control, not just those that sustain rule governance. For example, satire and theater has long been used to trim the over-reach of some social rules and indeed some rulers. Social groups with such institutions will likely be more flexible in rule governance and change.


This was a brief report from a distant island. Rules both enhance and restrict behavioral variability. Clinical practitioners have learned to undermine rigidity, avoidance, and the application of rules to areas that are not well rule-governed, and to promote cognitive flexibility, flexible attention to the now, and positive values choice and clarity. The first four of these promote healthy variation and the last two promote the selection of effective practices.  The clinical challenge is learning how to formulate and follow workable rules that are modifiable by experience, how to abandon rules that aren’t working, and when and how to rely more on intuitive or trial and error processes when rule-governance per se is not applicable. Some advances have been made in doing so, as meta-analyses of outcomes and processes of change suggest (e.g., Hayes et al., 2006).

The findings are one level of analysis need not apply to another, but often analogies can be drawn. Several possible extensions to the situation Ostrom describes seem possible, but whether they are worthwhile is an empirical question that can only be answered at that level of analysis.


Barnes-Holmes, D., O’Hora, D., Roche, B., Hayes, S. C., Bissett, R. T., & Lyddy, F. (2001). Understanding and verbal regulation. In S. C. Hayes, D. Barnes-Holmes, & B. Roche (Eds.), Relational Frame Theory: A post-Skinnerian account of human language and cognition (pp. 103-117). New York: Plenum Press.

Berens, N. M. & Hayes, S. C. (2007). Arbitrarily applicable comparative relations: Experimental evidence for a relational operant. Journal of Applied Behavior Analysis, 40, 45-71.

Bond, F. W. & Bunce, D. (2003). The role of acceptance and job control in mental health, job satisfaction, and work performance. Journal of Applied Psychology, 88, 1057-1067.

Bond, F. W., Flaxman, P. E., & Bunce, D. (2008). The influence of psychological flexibility on work redesign: Mediated moderation of a work reorganization intervention. Journal of Applied Psychology, 93, 645-654.

Chawla, N. & Ostafin, B.D. (2007). Experiential avoidance as a functional dimensional approach to psychopathology: An empirical review. Journal of Clinical Psychology, 63, 871-890.

Cheron, D. M., Ehrenreich, J. T., & Pincus, D. B. (2009). Assessment of Parental Experiential Avoidance in a Clinical Sample of Children with Anxiety Disorders. Child Psychiatry and Human Development, 40, 383-403.

Cohen, G. L., Garcia, J., Apfel, N., & Master, A. (2006). Reducing the racial achievement gap: A social-psychological intervention. Science, 313, 1307-1310.

Deacon, T. W. (1997). The symbolic species: The co-evolution of language and the brain. New York: Norton.

Devany, J. M., Hayes, S. C. & Nelson, R. O. (1986). Equivalence class formation in language‑able and language‑disabled children. Journal of the Experimental Analysis of Behavior, 46, 243‑257.

Dugdale, N. & Lowe, C. F. (2000). Testing for symmetry in the conditional discriminations of language-trained chimpanzees. Journal of the Experimental Analysis of Behavior, 73, 5–22.

Fresco, D. M., Williams, N. L., & Nugent, N. R. (2006b). Association of explanatory flexibility and coping flexibility to each other and to depression and anxiety. Cognitive Therapy and Research, 30, 201–210.

Ginsberg, S. & Jablonka, E. (2010). The evolution of associative learning: A factor in the Cambrian explosion. Journal of Theoretical Biology, 266, 11-20.

Hayes, S. C. (Ed.). (1989). Rule‑governed behavior: Cognition, contingencies, and instructional control. New York: Plenum.

Hayes, S. C., Barnes-Holmes, D., & Roche, B. (2001). Relational Frame Theory: A Post-Skinnerian account of human language and cognition. New York: Plenum Press.

Hayes, S. C., Follette, V. M., & Linehan, M. M. (Eds.). (2004). Mindfulness and acceptance: Expanding the cognitive behavioral tradition. New York: Guilford Press.

Hayes, S. C., Luoma, J., Bond, F., Masuda, A., and Lillis, J. (2006). Acceptance and Commitment Therapy: Model, processes, and outcomes. Behaviour Research and Therapy, 44, 1-25.

Hayes, S. C., Wilson, K. W., Gifford, E. V., Follette, V. M., & Strosahl, K. (1996). Experiential avoidance and behavioral disorders: A functional dimensional approach to diagnosis and treatment. Journal of Consulting and Clinical Psychology, 64, 1152-1168.

Lipkens, G., Hayes, S. C., & Hayes, L. J. (1993). Longitudinal study of derived stimulus relations in an infant. Journal of Experimental Child Psychology, 56, 201-239.

Luciano, C., Gómez-Becerra, I. & Rodríguez-Valverde, M. (2007). The role of multiple-exemplar training and naming in establishing derived equivalence in an infant. Journal of Experimental Analysis of Behavior, 87, 349-365.

McHugh, L. & Stewart, I. (2012). Self and perspective taking. Oakland, CA: Context Press / New Harbinger.

Mercier, H. & Spencer, D. (2011). Why do humans reason? Arguments for an argumentative theory. Behavioral and Brain Sciences, 34, 57-74.

Nichols, J. (1992). Linguistic diversity in space and time. Chicago: University of Chicago.

Nowak, M., & Highfield, R. (2011). SuperCooperators: Altruism, evolution, and why we need each other to succeed. New York: Free Press.

Nowak, M. A., Tarnita, C. E. & Wilson, E. O. (2010). The evolution of eusociality. Nature, 466, 1057-1062.

Palm, K. & Follette, V. M. (2010). The roles of cognitive flexibility and experiential avoidance in explaining psychological distress in survivors of interpersonal victimization. Journal of Psychopathology and Behavioral Assessment, 33, 79-86,

Seppala, P. (1989). Semi-autonomous work groups and worker control. In S. L. Sauter, J. J. Hurrell Jr., & C. L. Cooper (Eds.), Job control and worker health (pp. 291-306). Chichester: John Wiley & Sons.

Seyfarth, R. M., & Cheney, D. L. (2003). Signalers and receivers in animal communication. Annual Review of Psychology, 54, 145-173.

Sheldon, K. M., Ryan, R., Deci, E. & Kasser, T. (2004). The independent effects of goal contents and motives on well-being: It’s both what you pursue and why you pursue it. Personality and Social Psychology Bulletin, 30, 475-486.

Sidman, M. (1971). Reading and auditory‑visual equivalences. Journal of Speech and Hearing Research, 14, 5‑13.  

Skinner, B. F. (1966).  An operant analysis of problem solving (pp. 225‑257).  In B. Kleinmuntz (Ed.), Problem‑solving: Research, method, and theory. New  York: Wiley.

Steele, D. L. & Hayes, S. C. (1991). Stimulus equivalence and arbitrarily applicable relational responding. Journal of the Experimental Analysis of Behavior, 56, 519-555.

Tinbergen, N. (1963). On aims and methods of ethology. Zeitschrift fur Tierpsychologie, 20, 410-433.

Tomasello, M. (2008). Origins of human communication. Cambridge, MA: The MIT Press.

Tomasello, M. (2009). Why we cooperate. Boston: MIT Press.

Tomasello, M., Carpenter, J., Call, J., Behne, T., & Moll, H. (2005). Understanding and sharing intentions: the origins of cultural cognition. Behavioral and Brain Sciences, 28, 675-735.

Weil, T. M., Hayes, S. C., & Capurro, P. (2011). Establishing a deictic relational repertoire in young children. The Psychological Record, 61, 371-390.

Wells, A. (2000). Emotional disorders and metacognition: Innovative cognitive therapy. Chichester, UK: Wiley

Wenzlaff, R. M. & Wegner, D. M. (2000). Thought suppression. Annual Review of Psychology, 51, 59-91.

Williams, K. E., Ciarrochi, J. & Heaven, P. C. L. (in press). Inflexible parents, inflexible kids: A 6-year longitudinal study of parenting style and the development of psychological flexibility in adolescents. Journal of Youth and Adolescence.

Wilson, D. S. & and Gowdy, J. (in press). Evolution as a general theoretical framework for economics and public policy. Journal of Economic Behavior and Organization.

Wilson, D. S., & Wilson, E. O. (2007). Rethinking the theoretical foundation of sociobiology. Quarterly Review of Biology, 82, 327-348.

Wilson, D. S., Hayes, S. C., Biglan, T., & Embry, D. (under submission). Evolving the future: Toward a science of intentional change.

Published On: April 6, 2012

Peter Turchin

Peter Turchin

Curriculum Vitae

Peter Turchin is an evolutionary anthropologist at the University of Connecticut who works in the field of historical social science that he and his colleagues call Cliodynamics. His research interests lie at the intersection of social and cultural evolution, historical macrosociology, economic history and cliometrics, mathematical modeling of long-term social processes, and the construction and analysis of historical databases. Currently he investigates a set of broad and interrelated questions. How do human societies evolve? In particular, what processes explain the evolution of ultrasociality—our capacity to cooperate in huge anonymous societies of millions? Why do we see such a staggering degree of inequality in economic performance and effectiveness of governance among nations? Turchin uses the theoretical framework of cultural multilevel selection to address these questions. Currently his main research effort is directed at coordinating the Seshat Databank project, which builds a massive historical database of cultural evolution that will enable us to empirically test theoretical predictions coming from various social evolution theories.

Turchin has published 200 articles in peer-reviewed journals, including a dozen in Nature, Science, and PNAS. His publications are frequently cited and in 2004 he was designated as “Highly cited researcher” by Turchin has authored seven books. His most recent book is Ultrasociety: How 10,000 Years of War Made Humans the Greatest Cooperators on Earth (Beresta Books, 2016).

Leave a Reply

<textarea name="ak_hp_textarea" cols="45" rows="8" maxlength="100" style="display: none !important;">

This site uses Akismet to reduce spam. Learn how your comment data is processed.