Quantitative prediction and molar description of the environment.
Measure the full feedback loop, not single responses, to predict behavior change.
01Research in Context
What this study did
Baum (1989) is a theory paper. It says we must describe the whole environment before we can predict behavior.
The author wants big-picture feedback functions, not tiny moment-to-moment counts.
What they found
The paper finds that science can predict behavior only after we map how reinforcers flow over time.
Without molar data, our numbers stay weak.
How this fits with other research
VERHAVMOLLIVER (1963) started the quest. That lab study showed how to measure preference between two schedules. Baum (1989) widens the lens and asks for the same rigor in daily life.
Matson et al. (2011) backs him up. Their review of 173 functional assessments shows that attention, escape, and tangibles are the big feedback loops in classrooms and homes.
Matson et al. (2008) gives a live demo. In four children with Smith-Magenis syndrome, low adult attention triggered problem behavior and rich attention followed. The molar pattern matched the theory.
Wynne et al. (1988) shouts the same warning one year earlier: stop running weak studies and start measuring function with numbers.
Why it matters
Next time you write an FBA, graph the whole stream of reinforcement. Count how often attention, escape, or tangibles follow the target behavior across full sessions. That molar picture, not single responses, will let you forecast intervention success.
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02At a glance
03Original abstract
Molecular explanations of behavior, based on momentary events and variables that can be measured each time an event occurs, can be contrasted with molar explanations, based on aggregates of events and variables that can be measured only over substantial periods of time. Molecular analyses cannot suffice for quantitative accounts of behavior, because the historical variables that determine behavior are inevitably molar. When molecular explanations are attempted, they always depend on hypothetical constructs that stand as surrogates for molar environmental variables. These constructs allow no quantitative predictions when they are vague, and when they are made precise, they become superfluous, because they can be replaced with molar measures. In contrast to molecular accounts of phenomena like higher responding on ratio schedules than interval schedules and free-operant avoidance, molar accounts tend to be simple and straightforward. Molar theory incorporates the notion that behavior produces consequences that in turn affect the behavior, the notion that behavior and environment together constitute a feedback system. A feedback function specifies the dependence of consequences on behavior, thereby describing properties of the environment. Feedback functions can be derived for simple schedules, complex schedules, and natural resources. A complete theory of behavior requires describing the environment's feedback functions and the organism's functional relations. Molar thinking, both in the laboratory and in the field, can allow quantitative prediction, the mark of a mature science.
The Behavior analyst, 1989 · doi:10.1007/BF03392493