Practitioner Development

A mingled yarn.

Marr (1996) · The Behavior analyst 1996
★ The Verdict

Complexity theory gives you one set of rules to see both client behavior and staff systems as emergent patterns.

✓ Read this if BCBAs who like big-picture models and run multi-client or staff systems.
✗ Skip if Clinicians who need today’s protocol, not philosophy.

01Research in Context

01

What this study did

Smith (1996) wrote a think-piece. He asked: what if one set of rules explains both clouds and kids?

He pulled ideas from physics and biology. He stitched them into behavior analysis.

02

What they found

The paper says complexity theory can be our shared ruler. It measures living and non-living systems the same way.

Emergent patterns, feedback loops, and simple rules that create big effects are the core tools.

03

How this fits with other research

McDowell (2013) extends the idea. He shows a functional theory can predict behavior without mapping every brain wire. This keeps the spirit of complexity—simple rules, big predictions.

Jensen et al. (2013) swap the label. They plug in information theory instead of complexity theory. Same goal: one ruler for many domains.

Lalli et al. (1995) set the stage. They linked organic evolution to behavioral evolution one year earlier. Smith (1996) widens the lens from biology to all systems.

04

Why it matters

You can borrow complexity tools today. Map mand bursts on a feedback loop graph. Watch how one staff comment multiplies into a ward-wide behavior wave. If the pattern looks like a weather front, treat it like one: shift the initial conditions, not each gust.

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Plot one client’s tantrum data as a line graph; draw arrows for staff attention moments—look for repeating loops.

02At a glance

Intervention
not applicable
Design
theoretical
Finding
not reported

03Original abstract

The behavior of nonliving and living systems is generally viewed as being qualitatively different. The key difference is often summarized by saying that whereas living systems are complex, nonliving ones are simple. This distinction is often the basis for claiming essential differences in conceptual stances, methods, and theories between scientific fields. I argue first that nonliving systems can display the unpredictable, irreducible, irreversible, and emergent-in sum, complex-properties of living systems. Then I discuss an emerging field called complexity theory, the principles of which offer the promise of bringing quantitative unity to an enormous range of phenomena, living or dead.

The Behavior analyst, 1996 · doi:10.1007/BF03392736