In my last post, I have discussed the The Postulates of Linguistic Agreement. In this post, I will discuss how is it applied to scientific method.
Let’s first considering the following thought experiment.
Assuming someone who believes that before leaving the house everyday, tap the left foot three times will bring good fortune for the day. Then in the following two days two events happened.
- On the first day, the person tapped his left foot and left home. He lost a dollar on the side of the road on the way to work.
- On the second day, the person didn’t tap his left foot and left home. He found a dollar on the side of the road on the way to work.
Here is his reasoning for justifying his daily ritual: on the first day, the ritual has brought him good fortune, because if he has not performed it, he would have lost more money. On the second day, his failure of performing the ritual has brought him misfortune because he would have found more money if he has tapped his foot in the morning.
Many reader would agree with me on that this person’s belief is a mere superstition, and his reasoning is fundamentally flawed. But regarding why this fictional person’s reasoning is flawed may vary from person to person, and readers would further disagree if ever one of us makes similar mistakes in our everyday reasoning. But here, I will present my thoughts.
Interestingly, in the thought experiments above, the experimenter seems to have employed a scientific method. He controlled variables, in the two days, he has shown that when performs his daily ritual, fortune will follow, while failing to do so, misfortune will trail. So this demonstrates the first point I want to make here:
Scientific method that leads to truth is not just conducting controlled experiments then interprets data.
There are two major errors in the examples above:
- The definition of “good fortune” is ambiguous. This has violated the postulates of linguist agreement.
- To justify the outcome is “good fortune” or “bad fortune” the experimenter used hypothetical data (or extrapolated data, or fake data), to support his argument. He stated that “because if he has not performed it, he would have lost more money.” for instance. But that is not part of the observation.
In this post I will show how the ambiguity of language can raise problems in experiment designs and how does modern science overcomes that problem. In the example above, the ambiguity of the result or observation of “good fortune” allows the experimenter to retrospectively construct definitions that fits the observation after the experiments has been conducted, which makes all of the experimenter’s claim seemingly true. This fallacy is called “petitio principii” or more commonly mistranslated to “bagging the question”. In this fallacy implies the interlocutor argues the conclusion to be true by assuming it is true in the first place. In this case, because the experimenter retrospectively defined the “good fortune” to fit the observation, he is taking “this observation is good fortune” as part of his premises. Then after, he conclude “the observation is good fortune” as the result of the experiment.
For what we consider real science, such as physics and chemistry, here is the first rule of what makes their methods scientific:
1. The observation/measurement of an experiment must satisfy the postulates of linguist agreement
How physicists established this linguistic agreement, is using standardized measurements. It may sounds complicated, but everyone who has ever used a ruler is familiar with the standardized measurement concept.
Whether it is length, time, voltage, current, etc., all physical quantities are measured using a standard otherwise known as units. When we measure block to be 2 meters, what we mean is that when measured against a standard that we defines as 1 meter, the length of the block is equivalent to two of the standards (1 meter) adds together. From this example, we also see that one of the common uses of numbers is to describe a measured physical property in relationship to the defined standard. Here is how the application of units ensures the postulates of linguistic agreements. To reiterate the two postulates:
- For a given property (for example color), if A produces identical symbols in two different measurements, B must also produce identical symbols(though not necessarily identical to A‘s symbols)
- For a given property (for example color), if A produces different symbols in two different measurements, B must also produce different symbols(though not necessarily identical to A‘s symbols).
In the example of length, the symbol we produce is a number and a unit (2 m for example). For condition 1, consider two ropes x and y of the same length (say 2 m), no matter who measures the rope or even using a machine, we should get the same number for x and y within the small error margin. Whether it is 2 meters, 6.56 foot, or 78.74 inches, the measurement of the length of x and y should be the same. For the second condition, consider two ropes x and y, now of the different lengths, now the measurements for the length of x and y should be different.
It is not true that all measurements satisfy postulates of linguistic agreements. As the given example of the previous post, our human perception of color is a measurement of color, but it fails to satisfy postulates of linguistic agreements. For a theory to be called scientific, the observation or measurement it uses must satisfies postulates of linguistic agreements. This is a prerequisite to Karl Poppers‘ claim of reproducibility requirement for scientific method. Without agreement of the measurement, the scientific experiment is not reproducible. Considering the following scenario: A chemist describes the outcome of a chemical reaction as green, while another chemist describes the outcome of a chemical reaction as blue. We know that in some culture, the definition of the color green and blue are not identical, so they may actually seeing the same color, but disagree with the result! Similarly, we can see in some cases, the two chemists may actually see different shades of green but conclude that they have the same result.
I want to note here is that I don’t think there is a clear binary between what is scientific method and what is not. As I have noted in my previous post, perfect linguistic agreements is unattainable. Even with extremely accurate instruments, measurements are often subject to errors. Therefore instead of considering scientific method as a toggle switch, we should think of it more as a gradient. The closer linguistic agreement is achieved in measurement, more scientific the method is. Consider the evolution from alchemy to analytical chemistry, with more accurate symbolic representation and understanding of elements introduced to the field, more scientific, the field becomes.
In the next blog post, I will discuss the importance of observability of scientific method. I will try to explore whether it is possible to draw conclusions about things that we can not see, such as luck, and fate. Stay tuned.
Before I end the post, I want to point out a common mistake people make. We often consider mathematical equations are universally true. That is, when we use mathematics, we will always get the correct result. That is not true.
Take the example of 2 + 2 = 4. Many may say that it is objective and universally true. But what is 2 meters plus 2 inches adds to? 4 of what? 4 of 20.18504 inches? How about adding 2 squirrels to 2 hours? Does it equals to 4 of something? If so, what is that thing?
Mathematical equations produce correct result only when we apply it to the correct physical properties. When adding two meters to two meters, we do get 4 meters. But when we taken it out of context, or apply to the wrong context, we may still be able to do computations, but the results will be completely nonsensical. Argue all we want, but I think not many would agree with us that 2 squirrels to 2 hours = 4 squirous.
RhaPsoDySea 