Usually in every-day English we don’t need to bother with specifying which alternatives are being excluded when we make a statement about something. But Statements in Theorymaker are a bit more precise: we are required to list or somehow mention the alternatives. The point of this isn’t “added precision”. The point is to be able to construct Theories, to show how something being one way (rather than another) contributed to another thing being one way (rather than another).

The most affected area was  *East--* ((North, South, East, West)) Province.

This Statement says that the most affected area was East Province rather than any of the (three other) alternatives. The corresponding diagram has a black symbol to the left, one of various different shapes, which reminds that this is a real Variable we can observe or go out and measure or check; in this case the black symbol has a “jumbled brick” shape tells us that this is a Statement about an unordered or “nominal” Variable.

If you hover your mouse over the word “TEXT” to the top right of the diagram, you will see the equivalent written Theorymaker.

To talk and write clearly about cause and influence, it can be very helpful to specify the possible alternatives to our statements. In fact doing so can clear up a lot of problems and apparent paradoxes, see (Schaffer 2005).

(explain more about the contrastive theory of causation.)

Traditional Theories and Theories of Change hardly ever do this. Theorymaker does. Any Theorymaker Statement has to specify the possible alternatives. Quantitative social scientists would also normally insist, just like Theorymaker native speakers, on understanding key quantities as Variables. What makes Theorymaker particularly flexible is that Theorymaker native speakers don’t insist on using numerical scales.

The central concept of a Variable in Theorymaker already implies the idea of a counterfactual: whatever Level the Variable has now, it might have had any of its other Levels.

Every time we observe or report the Level of a Variable in Theorymaker, unlike in English, the grammar forces us to mention the other possible but not actual Levels, just as the grammar of English forces us to indicate, in every single sentence, the time that something happened .

So Theorymaker Statements are a way of talking about anything that could be different or could have been different, for which we may notice or record that it takes one Level where it could have taken another.

meta-Theorymaker: talking about Theorymaker

When we are talking about Theorymaker in this book, we will use some useful “Words in Capital Letters” like Theory and Statement as ways of talking about Theorymaker expressions and talking about evaluation: we call these special words “meta-Theorymaker”. When Theorymaker native speakers speak, you can actually hear the capital letters which they pronounce in a charming way which only expert non-native speakers can hope to approximate. Beginners should not even try. We can just stick to writing for now.

For example, the word “Effectiveness” introduced later (spelt with a Capital to make it clear that this is a Theorymaker word) is pretty similar to the existing English word “effectiveness”, but we hope English-speaking M&E people might actually find it an improvement, as we shall see.


A Statement is just like an English statement but with two tweaks. First, one part (the “factual Level”) is followed by a double hyphen and enclosed with stars (*); second, it is followed by a specification in double brackets of the alternatives (the “Levels”) which could go in place of the factual Level.


The traffic light is *orange--* ((red, orange, green))

The specification of alternatives can be explicit, e.g. “red, orange, green” or implicit e.g. “0-100”, or even vaguer - see xx.

The traffic light is *orange--* ((red, orange, green))

is equivalent to the English statement

“The traffic light is orange”

… but the alternatives are made more explicit than in English. You can also think of it as:

“The traffic light is orange (possibilities are red, orange or green)”

If more than one element is marked, e.g.

The traffic light is *orange,green--* ((red, orange, green))

this is equivalent to the English statement

The traffic light is orange or green. 


The child's height is *165cm--* ((positive continuous numbers))

is equivalent to the English sentence

The child's height is 165cm.


The child's height is *165 to 175cm--* ((positive continuous numbers))

is equivalent to the English sentence

The child's height is between 165cm and 175cm.

The corresponding Theorymaker diagrams look like, for example, this:

The traffic light is *orange--* ((red, orange, green))


The set of alternatives within double brackets in a Theorymaker Statement are called the Levels of the Statement.

We can also say that the set of all the Statements associated with one Variable is the set of Levels of the Variable.

Sometimes each member of the set is listed explicitly, sometimes it is indicated in other ways e.g. by specifying two extremes, e.g. “1-10”.

There may be an ordering of the Levels, specified implicitly or explicitly, e.g.:

The national security alert status is low ((low < medium < high))

The height of the child is 125 ((continuous number)) cm. 

Often, as in the case of a law being passed, or a project being funded, the only two Levels are “no” and “yes” (or “false” and “true”).

Whether the law is passed ((no, yes))

There are different ways of saying the same thing:

The law is ((not passed, passed))

In still other cases there is an explicit (or implicit) list of choices.

Current alert level ((green, orange, red))

Later, we will look at Variable-signs where we cannot actually list all the possible Levels, e.g. because “there are an infinite number of possible Levels”, such as distances, percentages, etc.

In an expression like *X--Y*, X is the factual Level (or Levels) of the Statement (or just “the Factual”)

So in the Statement I scored *20%--* ((0-100%)), 20% is the factual Level.

In the Statement I don't know my exact percentage but I know I scored *15 to 20%--* ((0-100%)), 15 to 20% is also the factual Level - even though this is a range of Levels rather than a single Level.


Theorymaker native speakers sometimes talk about Facts as well as Statements. So they say, the Statement which says “100 t-shirts were printed” is true because of the Fact that 100 t-shirts were indeed printed.

We will use the word Fact when talking about, loosely, what the Statement refers to: what makes it true. Theorymaker native speakers also say that the Statement reports the Fact.

A Fact is whatever makes a Statement true.

Why bother?

When doing M&E, we often need to write down the facts about a project and the hypothesised connections between them. Theorymaker provides a standard but flexible way to write these kinds of things down. The main point is that Theorymaker always puts variability front and centre. If you learn Theorymaker, you will see the Theorymaker way of seeing the world in terms of Variables is what helps them to be so good at understanding and talking about Monitoring and Evaluation.

On its own, this way of writing will probably seem like a bit of a waste of time. It comes into its own when we start to talk about Theories, contribution, attribution, etc.

To take a very simple example. In English we might say:

The alert status is now orange.

… which is fine. But assuming that the alert Levels are perhaps green, orange and red, A member of the Theorymaker tribe would say this:

The alert status is *orange--* ((green < orange  < red)).

A Theorymaker listening to or reading this phrase can glean even more information from it; the use of the < “less-than sign” shows that green is somehow less than orange, which is somehow less than red.

On the other hand, of course the Levels might be, say, white, green, orange and red. In which case a Theorymaker speaker would have no choice but to say:

The alert status is *orange--* ((white < green < orange  < red)).

So that does make a bit of a difference which a speaker of the Theorymaker language is forced to make clear - because of the way Theorymaker sentences work. They don’t have a choice6, just as in German or French (and plenty of other languages) you can’t opt out of declaring the grammatical gender of your nouns or in English (and plenty of other languages) you can’t escape distinguishing between singular and plural. Guy Deutscher gives an example from a South American language which has a massive array of grammatical markers which include not only information about how reliable my statement is but also where I got the information from. Both of these perspectives both get their own sets of tense-like markers et cetera, and the grammar of this language forces its speakers to make these distinctions in every single sentence they utter.

Of course in everyday life we get by just fine without worrying too much about these things. But as evaluators and M&E specialists we often have to think hard about causation and contribution, about measurement and counterfactuals, and we are going to have to be a bit more precise. This is the point of Theorymaker.

We are certainly not kidding ourselves that merely by adopting these new words we will eliminate all ambiguity in monitoring and evaluation, or even all relevant and significant ambiguity, or even that ambiguity alone is a big problem, because it isn’t. But we will be able to avoid some particular kinds of ambiguity which typically bother us when we try to talk about projects and their effects.


By convention, sometimes Theorymaker native speakers don’t bother with is, are etc when writing out their Statements. So this:

The colour of the traffic light is  ((red, orange, green))

… is equivalent to this…

The colour of the traffic light  ((red, orange, green))    

Also, Theorymaker native speakers have an alternative form for writing out so-called no/yes Statements, those which can only be true or false. So this:

The law on the new flag is ((not passed, passed))

… is equivalent to this…

The law on the new flag is passed ((no, yes))

Some Theorymaker native speakers also tolerate nominal or interrogative forms such as these:

Whether the law was passed ((true, false))

Was the law  passed ((no, yes))?

The passing of the law ((not passed, passed))


Schaffer, J. 2005. “Contrastive Causation.” Philosophical Review 114 (3): 327–58. doi:10.1215/00318108-114-3-327.

  1. Well, actually, they can in fact deal with incomplete sets of options too, see xx.