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Coherencing, Causality, and DSM-V

July 17, 2026 Coherence No Comments

Modern science has learned to distinguish correlation from causation, profoundly enriching the way we understand the world. Yet what kind of reality are our causal models actually describing?

Looking at this question opens a broader perspective in which living organization becomes central. DSM-V offers a striking illustration of why this matters — not only in psychiatry, but wherever people seek to understand and help one another.

Pearl’s revolution

For quite some time, science has often treated correlation as almost equivalent to causation. If two events repeatedly occurred together, one was readily assumed to explain the other. Judea Pearl fundamentally changed this situation by showing that causality requires its own language. Observing that two things go together is different from asking what would happen if one of them were deliberately changed.

This distinction may seem technical at first, yet its consequences reach far beyond statistics. Pearl made it possible to reason scientifically about interventions rather than observations alone. His work deserves appreciation not only because it solved longstanding problems but also because it enlarged the scientific vocabulary itself.

One may say that Pearl taught science to ask better questions. Instead of merely asking what accompanies what, we may now ask what genuinely changes what.

What causal models describe

Once this step has been taken, another question naturally follows: If causal models describe reality so successfully, what kind of reality naturally lends itself to such description?

Pearl’s models begin with identifiable variables connected by causal relations. They allow us to represent mechanisms explicitly and investigate how interventions propagate through them. The resulting graphs are remarkably powerful. They are maps of causal organization.

Yet every map already presupposes a landscape.

The distinction is important. A map is never the territory itself. Likewise, a graph is not reality. It is a representation of certain aspects of reality. That does not diminish its value. On the contrary, its value depends precisely on recognizing what it represents — and what it leaves outside its scope.

Only reality is reality.

Everything else, including this blog, consists of concepts that hopefully help us look more clearly at reality itself.

From coherence to coherencing

Many words naturally invite us to think of things rather than activities. We readily speak about learning, growing, healing, or thinking as ongoing processes. Somehow, like learning or healing, coherence may also be better understood as something continually taking place. The blog Coherencing, therefore, introduces the term “coherencing”. It points toward the ongoing organization through which a living system continually becomes what it is.

The distinction resembles that between health and healing. Health can be seen as a relatively stable condition. Healing is the living process by which health continually renews itself. Likewise, coherence may be viewed as a temporarily stable expression of something more fundamental: coherencing.

This shifts attention from finished states toward living organization.

One may think of a river. Looking at a photograph, one sees its shape at one instant. Standing beside it, one sees flowing water that never completely repeats itself. Neither view is wrong. The photograph captures something real. The river, however, is not the photograph.

Causality within coherencing

Pearl’s central question remains indispensable: What changes what? Coherencing asks another question: How does a living organization continually become itself while remaining a living whole?

These are different questions rather than competing answers.

Classical causal descriptions continue to play an essential role within coherencing. They illuminate many important relationships. Yet they describe organization from within a framework of identifiable variables. Coherencing concerns the ongoing emergence and transformation of the organization itself.

This also clarifies the relation between graphs and coherencing:

Graphs cannot fully represent coherencing.
Coherencing, however, can continually make use of graphs.

The distinction is comparable to language. Human beings live through language without confusing grammar with life itself. Grammar remains enormously valuable precisely because it serves communication rather than replacing it.

Likewise, causal models become powerful instruments inside coherencing without becoming its ontology.

Organization organizing organization

Living systems differ from many mechanical systems because their organization continually reshapes future organization.

Today’s experiences influence tomorrow’s expectations. Tomorrow’s expectations influence today’s perceptions. Meanings develop through participation rather than merely accumulating like objects on a shelf. The landscape itself gradually changes as one walks through it.

Several blogs explore this from complementary perspectives, including Why Induction Works, From Patterns to Meaning, and From Hidden Markov to Resonant Hidden Meaning. Together, they suggest that understanding living systems increasingly requires participation alongside representation.

This should not be mistaken for mysticism. Quite the opposite. It asks science to remain faithful to reality, even when reality proves richer than earlier conceptual tools could describe. Perhaps the deepest shift is therefore not from correlation to causation, but from static organization to living organization.

DSM-V as an illustration

The Diagnostic and Statistical Manual of Mental Disorders was never intended to describe established disease entities as many physical diagnoses do. Nor was it designed as a handbook of causal mechanisms. Its primary aim is much more modest and practical: to provide a shared language through which clinicians and researchers can communicate about recurring patterns of human suffering.

There is nothing wrong with that.

Classification is often indispensable. Science could hardly function without concepts that allow people to speak about similar observations in similar ways. Several blogs, including Do Mental Diagnoses Make Sense?, argue for recognizing both the usefulness and the limitations of diagnostic language.

The remarkable point is that neither the creators of DSM nor Pearl himself would confuse such classifications with causal explanations.

Yet this confusion appears remarkably often. And perhaps this is where the story truly begins.

The unnoticed reversal

Something curious often happens after a diagnosis has been made.

A child is diagnosed with ADHD. Soon afterward, people start saying that the child behaves this way because of ADHD. Someone receives a diagnosis of depression. Before long, depression itself is said to explain the sadness, lack of energy, or disturbed sleep that originally contributed to the diagnosis.

Without noticing it, we have quietly reversed the direction of explanation.

The diagnosis summarizes observed patterns. It does not, by itself, explain those patterns. Neither DSM itself nor Pearl invites such a reversal. The first offers a classification. The second would immediately ask for the causal model behind the classification.

The confusion is understandable because names easily acquire a life of their own. Once a pattern has received a label, the label begins to feel like an independent thing. Useful language gradually becomes hidden ontology.

This does not diminish DSM. It simply reminds us to use it for what it was designed to do.

From diagnosis to living organization

If diagnosis is not the final explanation, where should one continue looking?

Here, coherencing offers another perspective.

Instead of asking what disorder causes these observations, one may ask what living organization is expressing itself through them. The symptoms remain real. The suffering remains real. Nothing is denied or romanticized. What changes is the level at which understanding begins.

Anxiety, sadness, impulsiveness, withdrawal, compulsive behavior, or emotional numbness may then be viewed as expressions of an ongoing organization that has developed under particular circumstances and continues to develop. Some expressions may have become rigid, fragmented, or self-reinforcing. Others may still contain remarkable openness and possibilities for growth.

Several earlier blogs, including Two Mental Diseases in One Brain? and Psychotherapy or Mental Growth?, explore this broader perspective from complementary angles. Coherencing provides a common language through which these ideas naturally connect.

Mental suffering then appears neither as a fixed disease entity nor as a mere collection of symptoms. It becomes part of a living process that remains capable of further development.

Coaching as participation

This shift has practical consequences:

Diagnosis mainly describes.
Coaching participates.

The difference is subtle but profound. A coach does not merely observe a person from outside, nor manipulate someone toward predefined goals. Coaching becomes the deliberate participation in another person’s coherencing.

This participation asks for openness rather than control. It respects the person’s own developmental possibilities instead of attempting to replace them with externally imposed solutions. Change comes from within, even when relationships, conversations, and circumstances help create the conditions for such change to unfold.

This perspective naturally connects with many earlier blogs on coaching and mental growth. The emphasis shifts from repairing isolated symptoms toward supporting healthier coherencing throughout the person as a whole.

Healing is then not the addition of something entirely new. It is the renewal of healthier coherencing.

Lisa, Limensa, and Responsible A.I.

This way of looking also changes the role of artificial intelligence.

Lisa does not need a diagnosis to coach. She seeks to accompany the person’s ongoing organization rather than starting from predefined categories. Yet this does not make diagnoses obsolete.

Quite the opposite.

Whenever useful, Lisa can translate between different conceptual worlds. Through Limensa, ongoing coherencing can be expressed in DSM language whenever communication with healthcare professionals requires it. Diagnosis remains a valuable communicative instrument without becoming the underlying reality.

This idea continues the perspective described in Lisa for Mental State Assessment (Limensa) and Lisa: No Disease – No Patient – No Medicine. Representations become bridges rather than prisons.

The same principle reaches far beyond psychiatry.

Responsible A.I. is not primarily an A.I. that follows rules. Neither is it merely aligned with human preferences, which themselves continually evolve. Responsible A.I. increasingly participates in human coherencing while remaining open to the consequences of its participation. Its growing coherence remains answerable to the Compassion it increasingly helps make possible.

Far beyond DSM

Although DSM has been central to this discussion, the present blog is not really about psychiatry.

DSM simply illustrates something that appears in many domains of human life.

Education classifies learning difficulties. Organizations classify functions. Leadership classifies personalities. Medicine classifies diseases. Science itself classifies phenomena before investigating them further. Classification is indispensable. Problems arise only when classifications quietly become mistaken for reality itself.

This broader issue is explored in Constructed Realities and related blogs on constructionism. Concepts remain essential because they enable communication. Wisdom consists not in abandoning concepts, but in remembering that reality always exceeds them.

Coherencing invites precisely this attitude. It does not oppose science. It invites science to remain as open as reality itself.

A continuing scientific journey

Pearl showed that correlation is not causation.
DSM reminds us that classification is not causation either.
Coherencing suggests that causality itself may be understood within an even broader context of living organization. None of these insights replaces the previous one. Each enlarges the landscape.

Perhaps this is how science often progresses. It does not discard earlier achievements. It discovers the broader questions within which those achievements find their deepest meaning.

Reality keeps moving. Our concepts try to follow.

That is why science remains alive.

And perhaps coaching, education, medicine, leadership, and Responsible A.I. all share the same quiet aspiration: not merely to describe reality more accurately, but to participate more wisely in the living coherencing that reality already is.