One of the most disorienting parts of starting a PhD in social change is realising that the words everyone seems to use do not always mean the same thing. Theory of change. Change theory. Explanatory theory. Research philosophy. Ontology. Epistemology. Methodology. It can quickly feel like you have walked into a conversation that began years before you arrived.
That is exactly what this episode of Changemaker Q&A responded to: a listener question from a practitioner who had moved into academic research and suddenly found themselves needing to develop both a theory of change and an explanatory change theory as part of their doctoral work.
The episode unpacked a distinction that is rarely explained clearly enough, especially to people crossing over from practice into research. It also made the case that if you want to explain why change happens, rather than just describe what happened, you will eventually need to engage with research philosophy in a much deeper way than most people expect.
A theory of change is not the same as a change theory
The first crucial distinction is between a theory of change and a change theory.
A theory of change is usually practical and context-specific. It is the map you create for a project, intervention, organisation, campaign, or program to explain how you believe change will happen in that particular setting. It is often used in development, philanthropy, nonprofit strategy, advocacy, and program design.
Traditionally, theory of change has been approached in a very linear way. Practitioners identify the outcomes they want, then work backwards to specify the activities, assumptions, and causal pathway they think will lead there. In many organisations, this ends up as a neat box-ticking exercise, often in the form of a logic model.
The problem is that real change is rarely neat or linear. Complex social systems do not unfold according to perfectly sequenced steps. They are dynamic, relational, context-dependent, and constantly shifting. That is why the episode pushed back on conventional theory of change models and argued for something more like a dynamic map of a context: a living tool that changes as you learn more about the system, the people within it, and the conditions shaping what is possible.
A change theory, by contrast, is much broader. It is a theory about change itself. It helps explain how and why change happens, often at a more abstract or disciplinary level. Where a theory of change helps you plan an intervention, a change theory gives you the conceptual foundation for understanding what change is, how causality operates, and why particular kinds of transformations occur.
Put simply, theory of change helps you plan. Change theory helps you explain.
Why a theory of change alone is not enough for a PhD
One of the clearest insights from the episode was that a theory of change, on its own, is not usually enough to count as an original contribution to knowledge in a PhD.
That does not mean it has no place in doctoral research. It can absolutely be part of a PhD, especially if you are working with organisations, engaging in participatory research, designing interventions, or collecting rich empirical material through practice. But the act of producing a context-specific theory of change is not, in itself, a doctoral contribution.
A PhD requires something deeper. It requires explanation, theorisation, and a justified account of why things happen the way they do.
That is where explanatory change theory comes in.
If you are trying to build an explanatory theory of change, you are no longer just asking, “What pathway do I think will produce this outcome?” You are asking, “What actually explains the processes and mechanisms through which this kind of change occurs?”
That question takes you beyond planning and into philosophy.
Why research philosophy matters more than most people realise
The episode argued that if you want to build explanatory change theory, you cannot avoid engaging with your research philosophy.
All research operates from a paradigm, whether it names it explicitly or not. A research paradigm shapes how you understand knowledge, reality, and the methods you use to investigate the world. It typically involves three interconnected dimensions:
Epistemology asks what counts as valid knowledge and how we can know things.
Ontology asks what is real and what kind of reality exists.
Methodology justifies the research methods you use based on your epistemological and ontological assumptions.
In many fields, researchers are trained to focus heavily on methods while barely touching ontology at all. But when your research is concerned with change, causality, and explanation, ontology becomes unavoidable.
That is because explanation requires you to deal with what reality is like, not just with what can be measured or experienced.
The limits of positivism and interpretivism
To make this point clear, the episode contrasted the two dominant paradigms in the social sciences and natural sciences: positivism and interpretivism.
Positivism tends to privilege what can be observed, measured, and tested empirically. It is strong on observable data and often favours quantitative methods. But it tends to reduce reality to what can be measured, leaving little room for deeper causal explanation.
Interpretivism focuses more on subjective experience, meaning-making, and how people understand their worlds. It is often associated with qualitative methods and is powerful for understanding how people experience social life. But it can drift toward the idea that reality is entirely dependent on interpretation, which makes explanation of broader causal structures more difficult.
Both paradigms are useful in different ways. But if your aim is to explain why change happens in a complex social context, neither paradigm is fully satisfying on its own.
One risks reducing reality to what is measurable. The other risks reducing it to what is interpretable.
Neither goes far enough in dealing with causality.
Why critical realism offers a way forward
The episode then introduced critical realism as the paradigm that made explanatory change theory possible in the speaker’s own doctoral research.
Critical realism begins from a deceptively simple but powerful position: there is a real world that exists independently of our knowledge of it, but our understanding of that world is always partial, situated, and fallible.
This avoids the limitations of both positivism and interpretivism. It allows us to say that reality exists objectively, while also recognising that our knowledge of it is always mediated by human perspectives, concepts, experiences, and limitations.
What makes critical realism particularly helpful for explanatory research is its stratified ontology. It distinguishes between three levels of reality:
The empirical level is what we can observe, experience, and measure.
The actual level includes events and processes that occur whether or not we observe them.
The real level consists of the underlying causal powers, structures, and generative mechanisms that produce the events and experiences we encounter.
This matters enormously for change research.
If you only work at the empirical level, you can describe what happened. If you go to the actual level, you can begin to explain how processes unfolded. But if you want to explain why change happens, you need to dig down into the real level and identify the generative mechanisms at work.
That is exactly what explanatory change theory tries to do.
Explanation is not the same as description
A useful example from the episode was gravity.
You cannot directly observe gravity itself. What you can observe is its effects: a falling object, planetary movement, a body returning to the ground. Gravity is the causal law or mechanism that explains those effects, even though it is not empirically visible in the same way as the effects it generates.
The same logic applies to social change.
You might observe a community becoming more politically active, a policy campaign gaining traction, a movement fragmenting, or a program producing unexpected results. Those are empirical effects. But to explain them, you need to ask what generative mechanisms were operating underneath. Was it trust? Power? Social identity? Institutional rigidity? Collective reflexivity? Economic pressure? Cultural norms? Political fear? Structural exclusion?
Explanatory change theory is not satisfied with what happened. It asks what had to be true in the underlying reality for those outcomes to occur.
That is a different level of inquiry.
What this means for PhD researchers
For someone just beginning a PhD, this can feel like a lot. And the episode did not pretend otherwise.
Developing an explanatory change theory is a demanding intellectual task. It means you are not only collecting and analysing data. You are also reasoning about causality, making philosophical choices explicit, and trying to justify how you move from observed evidence to claims about deeper mechanisms.
That is why the advice in the episode was both ambitious and honest. Yes, this kind of work is possible. Yes, it can be transformative. Yes, it may allow you to produce something genuinely original and powerful.
But it is also hard. It takes time. It often requires reading beyond your discipline. And it usually involves periods of confusion, frustration, and rethinking.
That does not mean you are doing it wrong. It probably means you are doing the real work.
Where to begin if you feel completely lost
For researchers feeling overwhelmed, the most practical guidance in the episode was to begin with the right foundational texts.
A strong entry point into critical realism is Enlightened Common Sense, a posthumous collection connected to Roy Bhaskar’s work. It offers an accessible overview of critical realism as a movement and helps situate the paradigm without requiring you to jump immediately into the densest foundational texts.
From there, it helps to understand the three major waves of critical realism:
Basic critical realism, introduced by Roy Bhaskar, lays out the core ontology and philosophy of science.
Dialectical critical realism extends this into the social sciences and becomes especially useful for anyone working on social transformation, being, contradiction, absence, and change.
The philosophy of metaReality goes even deeper and may be relevant for some researchers, though not all social science projects will need to engage with it directly.
For those wanting something more applied, the episode also recommended Priscilla Alderson’s Critical Realism for Health and Illness Research as a particularly useful example of how critical realism can be translated into actual research practice in the social sciences.
The point was not that every doctoral researcher must become a philosopher. The point was that if you want to explain change rather than merely document it, you need enough philosophical grounding to justify how you are making sense of causality.
The bigger takeaway: explanation requires depth
Perhaps the biggest lesson from the episode was this: explanatory work requires depth.
It is relatively easy to produce descriptive accounts of programs, movements, interventions, and social issues. It is much harder to explain the mechanisms underneath them. That deeper work demands conceptual clarity, ontological courage, and a willingness to stay with complexity rather than flatten it.
For practitioners entering research, this can be especially challenging because they often come with strong real-world insight but limited exposure to the philosophical scaffolding that academia expects. Yet they also bring something incredibly valuable: a deep sensitivity to context, complexity, and lived systems. When that practical grounding is paired with rigorous philosophical inquiry, it can produce extraordinarily rich research.
That is ultimately what this episode offered. Not a shortcut. Not a simple formula. But a map for understanding why this kind of work feels so big, and why it matters.
If you are entering a PhD and trying to make sense of theory of change, change theory, and explanatory research, you are not lost because you are incapable. You are lost because you have stepped into some of the biggest questions in the social sciences.
And that is not a bad place to begin.
