Quote: Anyway, let me suggest "....without offering an explanation for how it works, it isn't a theory."
More scientific ignorance. Real science or hard science generates predictive theories that identify tested relationships between the values of cause and effect variables. Hard science neither produces nor requires explanations of how the causal relationships work.
Let's see what folks that actually understand a thing or two about what a "theory" is say:
From this BioTech dictionary":
In science, an explanation for some phenomenon which is based on observation, experimentation, and reasoning. In popular use, a theory is often assumed to imply mere speculation, but in science, something is not called a theory until it has been confirmed over the course of many independent experiments. Theories are more certain than hypotheses, but less certain than laws.
Even in plain old dictionary.com, the relevant definitions are in direct contradiction to Bergerson's claim:
A set of statements or principles devised to explain a group of facts or phenomena, especially one that has been repeatedly tested or is widely accepted and can be used to make predictions about natural phenomena.
The branch of a science or art consisting of its explanatory statements, accepted principles, and methods of analysis, as opposed to practice: a fine musician who had never studied theory.
Not opne - ever - to admit ignorance or basic error, Bergerson posts a typical condescending rejoinder:
Scientific analysis, in the end, always comes down to humans making decisions about the validity of scientific theories. It is important to recognize that there are only two known methodologies for making such decisions.
1. The hard science methodology where decisions are based on the results of open, objective, and independent falsify and replace analysis and
2. The subjective/authoritarian/political methodology where the validity of a 'theory' is based on the subjective personal opinions or voting by some set of individuals...
In other words, theories for which there exists supporting empirical evidence and provide explanations for the phenomenon in question are not 'hard' or 'real' science, whereas, assertions supported only by more assertions that have not yet been 'falsified and replaced' by other unsupported assertions are 'hard' or 'real' science. Incredible...
If any readers have even heard of "falsify and replace" analyses, or "hard science predictive theories", as described by Bergerson, please, let me know.
For example, if you search for "hard science predictive theories", do you think you will receive returns linking to CalTech or MIT or something? If you do, you will be wrong - you will receive links to posts by or about Bergerson.
If you search for "predictive theories" you will get a number of returns, many of which are not links to Bergerson's internet posts. You will find something interesting - you will find that "predictive theory" is a concept that is used frequently in computer science:
Ultimately, generating theories from your own research will provide the greater HCI [Human-Computer Interaction ] community with valuable knowledge. Theories and models that come about from your research will be one of three kinds:
Explanatory theories seek to explain the behavior of our world; they tend to provide a more conceptual model of the world. Predictive theories seek to predict outcomes based on the changing values of component variables. Predictive theories provide an extremely high level of utility to HCI, they allow designers to directly predict the outcomes of their designs on user performance variables. Generative theories generate guidelines and principles that provide useful and applicable knowledge and models. The type of theory a researcher intends to produce guides the selection of appropriate research methodologies.
Instead, we need to equip the HCI person with power tools for design. For me, that implies supplying HCI with supporting science in the form of predictive theories. Predictive theories are not merely frameworks. Predictive theories are things (which one person can tell to another) that can predict a situational or design consequence. Predictive theories are generative theories. They are ways of characterizing and hence organizing and constraining the design space.
This is how Bergerson uses the term - should we be surprised? Though he is very cryptic about his background and what he does, I have gathered that he has an engineering background and is involved with generating computer models of human behavior. That certainly explains why he insists on his definition of "predictive theory" and on the uber-utility of it - it is what he does, therefore, it has primacy over all things. Standard 'when all you have is a hammer, everything looks like a nail' mentality.
However, 'predictive theories' ala Bergerson, as such, have limited utility outside of computer science and perhaps chemistry and physics since they do not explain anything.
So, you can 'predict' how much a bar of a pure metal will expand if you raise its temperature by one degree Centigrade. Big deal.
But you cannot actually explain why it does that. In terms of scientific knowledge, what good is it to be able to 'predict' something without understanding the reasons why the phenomenon even occurs? And to suggest, no - demand - that such 'theories' are "true science" and all else is 'political' is absurd to the highest degree. In fact, I find such 'theories' fairly useless in any fields other than those that do not seek to understand or explain anything, and why one would demand that such limited 'theories' are the only 'true' science escapes me, and I question whether the term 'theory' should even be used for such things.
But back to the topic at hand -
I am still undecided - is it pathetic or infuriating that this fool keeps writing so confidently about "hard science" when it is obvious that he lacks even a basic grasp of scientific principles?