Commons, M. L., & Richards, F. A. (2002). Organizing components into combinations: How stage transition works. Journal of Adult Development. 9(3), 159-177.

This paper investigates the nature of transition between stages. The Model of Hierarchical Complexity of tasks leads to a quantal notion of stage, and therefore delineates the nature of stage transition. Piaget’s dialectical model of stage change was extended and precisely specified. Transition behavior was shown to consist of alternations in previous-stage behavior. As transition proceeded, the alternations increased in rate until the previous stage behaviors were “smashed” together. Once the smashed-together pieces became co-ordinated, new-stage behavior could be said to have formed. Because stage transition is quantal, individuals can only change performance by whole stage. We reviewed theories of the specific means by which new-stage behavior may be acquired and the emotions and personalities associated with steps in transition. Examples of transitional performances were. Contemporary challenges in the society increasingly call for transition to post-formal and post-conventional responses on the part of both individuals and institutions as the example illustrate.

The acquisition of a new-stage behavior has been an important aspect of Piaget’s theory of stage and stage change. Because of his controversial notions of stage and stage change, however, little research on these issues has taken place in the late twentieth century, at least among psychologists in the United States. The research that has taken place is being done by Neo-Piagetians. The neo-Piagetians more precisely defined stage, taking each of Piaget’s substages and showing that they were in fact stages. In addition, three postformal stages have been added. Similar changes were made with Kohlberg’s stages and substages. Commons, Richards, and Armon (1984) created a stage comparison table, comparing stage sequences from a number of different traditions, that stands today as the standard. This table shows that there is, essentially, only one stage sequence. Commons and Richards (1984a, b) presented their first General Stage Model at that time. Commons and colleagues (Commons, Trudeau, et al., 1998; Commons & Miller, 1998) later revised that model and expanded it downward, changing the name of the model to the Model of Hierarchical Complexity. Table 1a shows a complete list of the Orders of Hierarchical Complexity described in that model.

A developmental theory should account for three aspects of behavior: a) what behaviors develop and in what order, b) with what speed, and c) how and why development takes place. Transition concerns itself mainly with the speed of development, and with specifically how and why development takes place. A developmental theory must be able to account for simple as well as complex behaviors. Behavior-analytic theories of development have concentrated on explaining why development takes place (e.g. Bijou & Baer, 1961; Baer & Rosales, 1997). Under these theories development has been explained primarily in terms of contingencies of reinforcement. Such accounts have argued that the sequences in which behaviors develop are environmentally determined. According to behavior-analytic theories, any particular behavior is viewed as being “shapable” given the proper contingencies. As a result, sequences have been largely seen as consisting of only two steps, arbitrary, and easily changed. Behavior-analytic theories have been better at explaining relatively simple behavior (the behavior of nonhuman species, infants, and individuals who are mentally retarded or autistic) rather than complex behavior. For these reasons, such theories have tended to become marginalized as far as developmental psychology as a whole is concerned.

Developmental psychology as a whole has been concerned with what develops and in what sequence. The major theory that has dealt with the possible sequences in which behavior is acquired has been the mentalistic theory of Jean Piaget (e.g. Piaget, 1954, 1976). Stage transition has also been an important issue for both Piagetians and NeoPiagetians (Benack & Basseches, 1989; Fischer, 1980; Fischer, Hand & Russell, 1984; Fischer et al., 1990; Piaget [as cited in Flavell, 1963]; Riegel, 1973).

Commons and Miller (1998) proposed a quantitative behavior-analytic theory of development that deals both with the sequences of development, and with why and how development takes place. The theory presented here is behavioral because it makes only behavioral assumptions and avoids mentalistic explanations. The theory also uses principles derived from quantitative analysis of behavior (e.g., Commons & Nevin, 1981) in that the assumptions are explicit and the measures of performance are quantitatively describable; neither are limited by the earlier forays into quantification such as those of Hull (1943; 1952) or Piaget (Inhelder & Piaget, 1958; Piaget, 1954; 1976; Piaget & Inhelder, with Sinclair-de Zwart, 1973).

In order to make the necessary arguments about stage transition, it is important first to present an outline of the Model of Hierarchical Complexity.

The Model of Hierarchical Complexity

The Model describes a new dimension of complexity that is at right angles to the traditional concept of Horizontal complexity (as seen in information processing). The Model is a cross-domain, or universal system that classifies the task-required hierarchical organization of responses. Every task contains a multitude of subtasks (Overton, 1990). When the subtasks are completed in a required order, they complete the task in question. Therefore the model asserts that all tasks fit into some sequence of tasks, making it possible to determine at what order of hierarchical complexity an ideal action would have to be to address that task.

In this task-complexity theory, for one task to be more hierarchically complex than another, the new task must meet three requirements (Commons, Trudeau, et. al., 1998). The new task-required action must:

(1) be defined in terms of the lower-stage actions;

(2) co-ordinate the lower-stage actions; and

(3) do so in a nonarbitrary way.

To expand a little on these statements, the first one says that the very definition of a task-required behavior with a higher complexity must depend on previously defined, task-required behavior of lower complexity. Second, the higher-complexity, task-required actions must co-ordinate the less complex actions. To co-ordinate actions is to specify the way a set of actions fit together and interrelate. The co-ordination specifies the order of the less complex actions. Third, the co-ordination must not be arbitrary. Otherwise the co-ordination would be merely a chain of behaviors. The meaning of the more complex task must not be severely altered by any non-specified alteration in the co-ordination.

Through such task analysis, the hierarchical complexity of a task may be determined. The hierarchical complexity of a task, therefore, refers to the number of concatenation operations it contains. An order-three task has three concatenation operations. A task of order three operates on a task of order two and a task of order two operates on a task of order one (a simple task).

Tasks are also quantal in nature. They are completed either correctly or not at all. There is no intermediate state. The order of hierarchical complexity is stepped just like the rings around the nucleus. Each level of task difficulty has an order of hierarchical complexity required to complete it correctly.

Because the Model of Hierarchical Complexity proposes a quantal notion of stage, this proposal also delineates the nature of stage change. We will show how this model allows a precise specification of Piaget’s dialectical model of stage change. We also discuss specific means by which new-stage behavior may be acquired and what may stand in the way of stage change.

Combinations of Lower-Order Actions

Because the Model of Hierarchical Complexity proposes that stage change consists of combining old actions into new ones, it is important to discuss the number of different kinds of combinations of lower-order actions that can occur. There are iterations, mixtures, chains, and new-stage behavior. Iteration is doing the same action over and over. For example, adding 2 + 3 + 4 + 1 is an iteration of adding. Mixtures of actions may include doing a problem set containing simple addition and simple multiplication tasks. Under chains can be included the ordering of subtask actions. However, chains have an arbitrary order to them. For example, people learn to wash the dishes and then take out the trash. But in reality, people could take out the trash and then do the dishes if they so wished, making the order reversed. The tasks can be done in any order, but people choose to do them in a certain fashion. Finally when the behaviors are combined in a non-arbitrary order, then one may have new-stage behavior (as opposed to a chain). Now the specific steps of combining behaviors in a non-arbitrary way will be described.

The Transition Steps

Piaget suggested a dialectical theory of transitional steps. To describe transition, this model elaborates on and systematizes the dialectical strategies described in the Piagetian probabilistic transition model (Flavell, 1963, 1971). The systematization of the substeps is based on choice theory and signal detection (Richards & Commons, 1990). While, as we have said, every task can contain a multitude of subtasks (Overton, 1990), for purposes of this illustration consider just three subtasks, A, B, and C.

In the Piagetian conception of transition from one stage to the next, the following steps were said to occur:

1. A, B (or not A).

2. A or B

3. A with B

A is an action from the previous stage. B is a complementary action or the negation of A. For example, A might be addition actions from the primary stage. And B might be the multiplicative action. When presented with the problem 2 x (3 + 4), the steps would be to assert A, assert B, alternate A and B depending on the situation, and finally, co-ordinate A with B.

Two elaborations of this model have been carried out within the Model of Hierarchical Complexity. First, two steps have been added. This first elaboration uses and is directly based on Piaget’s model of transition (Flavell, 1963, 1971). Second, we have added substeps (0, 1, 2, 3 and 4) to the third step. The substeps are based on Kuhn & Brannock (1977) and the systematization of that by Commons and Richards (1984b). The reconfigured theory looks as follows:

Step 4. A (Piaget’s Step 1)

Step 0. A fails (New step)

Step 1. B (or not A) (Piaget’s Step 1)

Step 2. A or B (Piaget’s Step 2)

Step 3. Smash A and B together (New step)

Step 4. A with B forming a new action C (Piaget’s Step 3)

Substeps 0, 1, 2, 3, 4 of Step 3 describe different ways of smashing A and B together, without fully co-ordinating them.

These steps are shown and described in more detail in Table 2. Note that Steps 0, 1, and 2 represent deconstruction, while Steps 3 and 4 represent construction.

Table 2

Deconstruction in the Transition Steps

Step	Sub-step	Relation	Name	Dialectical Form
0 (4)		A = A' with B'	Failure–old equilibrium point (thesis)	Previous stage synthesis does not solve all tasks. (Deconstruction begins.) Extinction Process
1		B	Negation–or complementation (antithesis)	Negation or complementation, Inversion, or alternate thesis. Subject forms a second synthesis of previous stage actions). (Antithesis.)
2		A or B	Relativism– (alternation of thesis and antithesis)	Relativism. Alternates among thesis and antithesis. The schemes co-exist, but there is no co-ordination of them. (Alternation of thesis and antithesis.)

Construction in the Transition Steps

3		A and B	Smash– (Attempts at synthesis)	The following substeps constitute transitions in synthesis.
	1		Hits and Excess False Alarms and Misses	Components from A and B are included in a non-systematic, non-co-ordinated manner. Incorporates various subsets of all the possible components.
	2		Hits and Excess False Alarms.	Incorporates subsets producing hits at stage n. Basis for exclusion not sharp. (Overgeneralization.)
	3		Correct Rejections and Excess Misses	Incorporates subsets that produce correct rejections at stage n. Produces misses. Basis for inclusion not sharp. (Undergeneralization.)
4(0)	4	A with B	Temporary equilibrium (synthesis and new thesis).	New temporary equilibrium (Synthesis and new thesis.)

The underlying process of transition is the increasingly rapid alternation back and forth between A and B. Yan (2000) presented data showing that an increased rate of alternation resulted in a new correct response that was stable. Performance, like the tasks themselves, is quantal in nature. That is, there are no intermediate performances. “Smash,”attempts to synthesize both A and B, however they are not coordinated. The combinations of old-stage actions are alternating, but only with the correct coordination is there the new-stage behavior that fits A and B together successfully. This is another way to explain why one cannot make tasks that fill the gaps between stages.

How to Measure Transition

Transition can be measured using at least four different methods:

1. Scoring interviews directly for statements that reflect transition

2. Finding the rate and acceleration of alternations of old-stage and newer-stage actions.

3. Finding the proportion of new-stage versus old-stage behavior.

4. Determining the hierarchical complexity of stimulus items (or tasks) and using a Rasch analysis to show that they form a continuous scale. Rasch (1980) analysis scales performance and items on the same log linear line. Transitional performance is shown by the mixtures of performances at different stages. The mixtures range from 0% at the higher stage to 100%. We call 95% at a stage consolidated performance and 0% up to 95% transitional. The advantages of the Rasch analysis are that: (a) it reduces measurement variance to a minimum, (b) and thus yields direct comparability. This is useful in assessing the nature of the items used to measure performance; the possible natural number order of hierarchical complexity of each item, and the corresponding stage of performances on each item. (Mislevy & Wilson, 1996; Spada & McGraw, 1985; Wilson, 1989).

Examples of Stage Transitions

In the current paper, we have measured transition by putting into operation the first method. We have collected a number of examples from three separate data sets. One data set, “Attachment” consisted of interviews on loss that were done with children (8-9 years of age) and adults (Miller & Lee, 2000; Miller, Lee & Commons, June, 2000). The second data set, “Therapy” (Wolfsont, June, 2000; Wolfsont, this issue) was taken from a study of the effects of a “brain gym” (see appendix) on stage change in adults. The third data sets, “Moral Reasoning”and “Good Education” (Commons, Danaher, & Meaney, June, 2000) consisted of moral-reasoning and “good education” (Armon, 1984) interviews of faculty and administrators from Harvard University (Commons, in preparation). Each of these data sets have been coded by three individuals using the Stage Scoring System (Commons, Danaher, et. al., 2000). In all cases, the reasoning has been categorized according to the stage of the responses of the subjects and to the types of transition examples found in it. These examples are presented in the appendix in the order of increasing stage and step.

They show some support for the steps of transition, as described above. Every subject’s behavior could be categorized with respect to a given transition step. This demonstrates the existence of the transition steps, but says nothing about other matters, such as how long someone may stay in a step or whether the sequence is valid as proposed. The remainder of the paper addresses the impact of emotions, personality, and various forms of environmental support on transition.

What Helps and Impedes Transition

Stage transition is slow. Very few people traverse 12 stages by the time they reach the age of 24. For example, Armon and Dawson (1997) showed that, at most, people are transitioning roughly every two years. The function is more linear in log time, however. The only time where there is very fast transitioning is perhaps during infancy. There are several aspects of situations and of persons that explain why people do not transition more rapidly and what emotions are associated with functioning within a given step. The simplest explanation is that there is a huge gap in difficulty between any two tasks differing in one order of hierarchical complexity. It is difficult to acquire a new-stage behavior when the initial rate of success of performing the next-stage behavior is so low. Dawson, Commons, and Wilson (in preparation) found that most people behaved at their most frequent stage of performance almost all of the time. This leaves very few behaviors at the higher stage to reinforce. Society simplifies the environment to fit the stage-appropriate order of hierarchical complexity. Preschools do not require writing, elementary schools do not require calculus, children are not asked to vote in public elections.

During transition, the perceived rate of reinforcement drops at the beginning. The more one confronts failure, the more one might expect avoidance. In fact, Commons, Grotzer, and Davidson (in preparation) found that feedback alone on order-of complexity tasks led to a decrease, rather than an increase, in stage of performance. One would expect that a defensive behavior, which involves fear of going through the steps, would decrease stage performance. These defensive actions have been seen to exhibit characteristic and associated emotions. Another explanation could be that one might never perceive in others a stage of performance higher than one’s own. Such an eventuality would impede learning through support. Finally, it may also be the case that organizations and institutions in fact punish higher-stage performances. Punishment usually strengthens behaviors that compete with the punished behavior and therefore maintain or even increase the avoidance of making next-stage behavior.

Transition Emotions

Every task has some order of hierarchical complexity. Testing performance on that task measures stage. If one performs the task successfully, that means one is operating at that stage. Therefore, static coping is what occurs when one is not required to perform above one’s characteristic stage of performance for such tasks. To meet or solve other problems successfully, however, requires one to change from one stage to the next. By contrast, dynamic coping is about changing stage. Different emotions will be associated with each step of transition. Recall that during the first three steps (0-2) deconstruction of previous stage behavior takes place (see Swan & Benack, this issue, for an example). During the last 2 steps (3-4) there is construction of new-stage behavior.

At the final step 4 (A with B) of the transition to the next stage, the closure makes one feel personally satisfied. As Rosenberg (1979) points out, how this momentary stability is perceived will effect how one feels socially. Quite often the demands for further development arise. This affects how long such positive feelings persist.

At step 0 (A), the demands for performance beyond the final step of the last stage are perceived. Without changing performance from step 4 of the previous stage, there is a perceived reduction of reinforcement for task performance. This is step 0. A person feels stupid and upset or angry after failing to fulfill a task. They may also continue to feel happy and elated about task mastery of the previous stage’s tasks.

At step 1 (B) the person feels dejected in addition to the previous feelings of anger (of being upset). In both of these first levels or stages of reactions, one just wants to “give it all up” and forget about it all. These are defense mechanisms, ways of switching the point and rejecting frustration.

At step 2 (A or B), a key word is relativism. One sees the possibility of solving a problem, but does not necessarily know the right means of doing it. Someone can be seen as competent for a special task, but not for just any task. Relativism has to do with contexts, and, because contextualization is somewhat concretizing, it is an attempt to cope with each context one confronts in the optimal way for that context. But concretizing is not the same as co-ordination. In concretization one knows only that there is a way of comparing situations and means, but not how to compare.

At this step, one may feel conflicted, anxious, and not sure of anything, because one really has no sense of control over the situation. People may ask themselves whether they are independent or dependent, but most probably cannot find an answer. Who is the one that really holds the reins? One might enjoy the excitement of the uncertainty, such as when a tourist visits a strange land and experiences other cultures for the first time. One might defend the relativism of such a situation as a necessary reality and feel that it justifies one’s behavior.

At step 3 (A and B) people begin to show more creativity in handling problems. There are three conditioning substeps.

The first substep is described as “getting chaotic.” One simply tries anything to get going. What is often done is just to smash (or to lump) all the existing systems of acting together without any formal integration. Smashing connotes aggressive and desperate attempts to “survive”– e.g., like the experience of having to build a life raft out of anything at hand. On the first substep, people feel somewhat manic as part of the normal process.

The second substep is the “learning what to do” substep. Templates are formed that are inclusive. The instance of the relationship at the target stage will be detected and used. This second substep brings with it a beginning to produce correct results. One is not yet able to eliminate those acts that do not bring good solutions, but the right direction is at hand. The most common feelings experienced at this point are excitement and a sense of frustration (from making errors).

The third conditioning substep is “learning when and where to do” each subset of action. People may feel uncomfortable and confused, but not helpless. They feel they know what to do, but not when to do it. On the other hand, people who do not know what to do may have a feeling of deep incompetence and helplessness. When people feel both confused and helpless, they have no sense of power or ability to act progressively.

In this substep one comes to learn to eliminate overgeneralization errors. One may be obsessive, fussy, and “a stickler.” Everything has to be compulsively cleaned up. Templates constructed here exclude, rather than include. Reconstruction takes place. There may be a sense that one is just not meant to get stuck in one’s present state or situation.

In the fourth conditioning step (A with B), inclusion and exclusion templates are finally co-ordinated. One may feel glorious and ecstatic for combining right components successfully. A post-reinforcement pause may follow.

Personality and Transition in Performance

It is proposed that there are given personality types associated with being frozen at a particular step. This relationship between personality and moving through transition is not necessarily a causal one. That is to say, a given personality type does not necessarily cause a person to stop during transition at a particular step. But it does suggest that a person with a given personality type might be more comfortable being frozen at a given step. Table 3 shows a highly speculative proposal for what the personality types might be. It is based mainly on my own observations of people during transition and informal discussion.

Table 3 Personality type and transition step

Step 0	Fault-finders	At low orders of performance in the social domain, this may result in antisocial behavior. These people perceive tremendous unfairness. People become “stuck” at this point because much of their current-order behavior is maintained by “punishment” that reinforces the failure behavior. They have experienced a huge drop in perceived reinforcement rate because they see the failures of their own behavior (at the present stage) to obtain what other people do obtain with next-stage behavior. They quite often have unshakable negative depressive scripts.
Step 1	Naysayer	May be persons who enter therapy, or rebels, radicals, or malcontents. They have given up their old ways. If A is wrong, then the opposite of A is right. After Step 0, this has the second largest drop in reinforcement rate. This occurs because they drop their previous successful behavior from A and substitute behavior from B for it.
Step 2	Relativists	Clinically speaking, at worst, these may be narcissists (“Situationalists”) or borderlines. That nothing works consistently proves no one loves them enough. In U.S. culture, it is quite often the largest group. They fill academia. They stop progress by insisting that there is more than one way to look at things, but they cannot come to a decision about such issues. Varying whether to behave A or B, this group gains some in reinforcement over groups in earlier steps. But the conflict between whether to chose A or B produces in them anxiety, mood swings, and uncertainty about roles, values etc.
Step 3	Movers	They are moving from smash to consolidate. They create great trouble for themselves and others by throwing ideas and actions together in a creatively haphazard way, taking a great deal of risk.
Step 4	Unshakable	Everything is okay, even if it is not okay. They avoid conundrums, apparent contradiction, comparisons to people they look up to. Anything is good enough.

When the rate of behavior reaches a maximum–most closely matching the rate of an expert–the behavior is deemed to be fluent. Even moderate numbers of errors in performance have long disappeared when rates of behavior may increase greatly. If it is over learned to the extent that very little effort or special attention is required, then the performance is deemed automatic. Fluency training on the components seems to increase the speed at which compounds are acquired from components. The implications of this work are that Precision Teaching in behavior analysis provides an empirical account of development.

The Upper Limits of Stage Transition

This discussion may make it sound as if, under ideal conditions, there is nothing in the stage transition theory we have presented that necessitates an upper limit on stage transition. The current formulation includes 14 orders of complexity as shown in Table 1. This formulation suggests that the number of times a series of components can be turned into a higher-order combination is presently 14. This may be the upper limit, at least for human beings. There have been an increasing number of empirical reports that there is a limit to the number of times a series of components can be turned into a combination. These reports can be found in training studies (e.g. Colby & Kohlberg, 1987), which show that at a given age, there are limits to how much training is effective in bringing about change. We also know, from training graduate students, that no matter how much training one gives graduate students, some never move beyond the systematic stage in their problem solving.

We suggest also that whatever the upper limit may be for any given individual, that limit seems to be almost totally heritable. For example, there does not seem to be any variation among identical twins who have been given training (Bouchard, 1990; Bouchard, Lykken, McGue, & Segal, 1990, 1991). When there has not been enough training, giving both twins training only causes acceleration in the slower twin – hence, the ceiling.

Conclusion

We have shown how the Model of Hierarchical Complexity leads to a quantal notion of stage, and therefore delineates the nature of stage transition. Piaget’s dialectical model of stage change was precisely specified. Transition behavior was shown to consist of alternations in previous-stage behavior. As transition proceeded, the alternations increased in rate until the previous stage behaviors were “smashed” together. Once the smashed-together pieces became co-ordinated, new-stage behavior could be said to have formed. Stage transition was shown to be quantal; that is, no matter what the nature of the intervention or where in transition one undergoes it, there cannot be intermediate performances. Individuals can only change performance by whole stage. We reviewed theories of the specific means by which new-stage behavior may be acquired and the emotions and personalities associated with steps in transition. Examples were provided.

The theory presented here and in other papers on the Model of Hierarchical Complexity (Commons, et. al, 1998) makes seven predictions, all of which Dawson, Commons and Wilson (in preparation) have confirmed:

1. There are exactly six stages from the beginning of schooling to adulthood in which we find participants performing.

2. Sequentiality of stage is perfect.

3. Absolutely no mixing of stage scores takes place. A Saltus model (Wilson, 1989) shows that there is no continuity between the stage items.

4. Gaps in difficulty exist between stages.

5. These gaps are relatively equal, showing that the task demands of transitioning from one stage to another are similar regardless of the particular transition. These gaps have been shown using a Rasch analysis with a Saltus model. This result is consistent with our argument here about the unstable quantal nature of transition..

6. People generally perform in a uniform manner. Most performances are predominantly at their most frequent stage of performance.

7. The distribution of person performance within each transition is strongly skewed toward the higher stage. Comparatively few people exhibit only a little reasoning at their highest stage. For example, there are fewer participants performing in transition on Kohlberg’s Heinz and Joe dilemmas and more consolidated performers. Whether a participant’s performance was in transition was measured psychometrically by the proportion of new-stage versus old-stage behavior.

Our task now is to fit together the various ways of measuring transitional performance and to examine the effects of intervention studies on transition.

Acknowledgment

Portions of this paper were presented at The Society for Research in Adult Development, Sunday, June 28, 2000, 9am to 10:20 am Pace University, New York City, New York. © Dare Association, Inc.

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Draney, K. L. (1996). The polytomous Saltus model: A mixture model approach to the diagnosis of developmental differences. Unpublished doctoral dissertation, University of California at Berkeley, Berkeley, CA.

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Fischer, K. W., Hand, H. H., & Russell, S.(1984). The development of abstractions in adolescents and adulthood. In M. L. Commons, F. A. Richards, & C. Armon (Eds.). Beyond formal operations: Late adolescent and adult cognitive development (pp. 43-73). New York: Praeger.

Fischer, K. W., Kenny, S. L.(1986). Environmental conditions for discontinuities in the development of abstractions .In R. A. Mines, & K. S. Kitchener (Eds.), Adult cognitive development: Methods and models.(pp. 57-75). New York: Praeger.

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Grotzer, T. A. McCarthy, K. G., Frome, K. W., & Commons, M. L. (June, 1987). The process of stage change. Paper presented at Beyond Formal Operations 3: Positive development during adolescence and adulthood. The Development of Adolescent and Adult Thought and Perception, Harvard University, Cambridge.

Herrnstein, R. J. (1982). Melioration as behavioral dynamism. In M. L. Commons, R. J. Herrnstein, & H. Rachlin (Eds.), Quantitative analyses of behavior: Vol. 2. Matching and maximizing accounts (pp. 433-458). Cambridge, MA: Ballinger.

Herrnstein, R. J., & Vaughan, W., Jr. (1980). Melioration and behavioral allocation. In J. E. R. Staddon (Ed.), Limits to action: The allocation of individual behavior (pp. 143-176). New York: Academic Press

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Lovell, C. W. (In press). Development and disequilibration: Predicting counselor trainee gain and loss scores on the Supervisee Levels Questionnaire. Journal of Adult Development.

McAuliffe, G. J. (In press). Student changes, program influences, and adult development in one program of counselor training: An exploratory inductive inquiry. Journal of Adult Development.

Miller, P. M., Lee, S. T., & Commons, M. L. (June, 2000). Scoring for stage and transition of losses in children and adult’s lives. Data presented at Society for research in Adult Development Symposium, Pace University, New York City, New York.

Miller, P. M., &. Lee, S. T. (June, 2000). Stages and transitions in child and adult narratives about losses of attachment objects. Paper presented at the Jean Piaget Society. Montreal, Québec, Canada.

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	Order or Stage	Discriminations	Vocalizations
0	calculatory	Exact–no generalization	none
1	sensory & motor actions	Rote, Generalized	Babbling (Universal)
2	circular sensory-motor actions	Open-Ended Classes	Phonemes
3	sensory-motor	Concepts	Morphemes
4	nominal	Relations among concepts	Single words: ejaculatives & exclamations, verbs, nouns, number names, letter names
5	sentential	Imitates and acquires sequences. Follows short sequential acts	Pronouns: my, mine, I; yours, you; we, ours; they, them
6	pre-operational	Simple deduction but contradiction is not excluded. Follows lists of sequential acts	Connectives: as, when, then, why, before
7	primary	Simple logical deduction and empirical rules involving time sequence. Simple arithmetic	Times, places, acts, actors
8	concrete	Full arithmetic	Interactions, social events, what happened among others

9	abstract	Discriminates variables such as Stereotypes; Logical Quantification; (all, none, some)	Variable time, place, act, actor, state, type; Quantifies (all, none, some); Categorical assertions (e.g., "All teachers do that!").
10	formal	Argue using empirical or logical evidence. Logic is linear, 1 dimensional.	Words: linear, logical, one dimensional, if... then, thus, therefore, because.
11	systematic	Constructs multivariate systems and matrices, coordinating more than one variable. Events and ideas situated in a larger context.	Systems: legal system, society, our company, the economy, the country.
12	metasystematic	Integrates systems to construct multisystems. Compare systems and perspectives in a systematic way (across multiple domains). Reflects on systems.	Metalogical, meta-analytic. Properties of systems named: homomorphic, isomorphic, incomplete, inconsistent or consistent, incomplete or complete, commensurable, incommensurable
13	paradigmatic	Discriminates how to fit metasystems together to form new paradigms	Paradigmatic. Limitations of metasystems explored. Paradigms of metasystems elucidated. Phenomena discovered
14	cross-paradigmatic	Discriminates how to form new fields by crossing paradigms.	New fields synthesized out of paradigms.