What is a Scientific Model?
I think it would be relevant, for the first blog post in this set, to discuss the what exactly we (meaning scientists and others) mean what we mention models. There are a lot of misconceptions about what a model is and there are many models that people don’t even realize are models. So, let’s start with the definition of a model. According to Brittanica, a model is:
I think the definition by Britannica does a pretty good job at representing what I will be referring to when I discuss models, but there are some details missing that I’ll discuss in later blogposts. So, let’s break this down and go through each part individually. “… the generation of a physical, conceptual, or mathematical representation of a real phenomenon that is difficult to observe directly.” So, what does this sentence tells us? Most importantly it illustrates that a model is a representation of real phenomenon. The key here is representation. Models are never going to be 100 percent accurate and assumptions and simplifications must always be made when designing models. Thus, it is a representation and not a duplication. The latter part of the sentence ascribes a reason for models and that is to represent phenomena that are “difficult to observe directly”. I think this piece is particularly apt for anyone thinking about modelling because it describes an essential question one must ask when thinking about models; Why should I make a model? Most often, the main reason why one decides to design a model is because the question proposed is experimentally intractable and/or exceedingly difficult or impossible to observe or conduct. Since you cannot directly answer your question through an experiment or observation, a model provides an alternative avenue to explore your question. “Scientific models are used to explain and predict the behaviour of real objects or systems and are used in a variety of scientific disciplines, ranging from physics and chemistry to ecology and the Earth sciences.” This sentence ascribes a function for modelling. While models are indeed designed to study difficult to observe phenomena, their role in this “study” is to explain and predict some aspect of the system[1] in question. The behaviour of objects or systems is a reference to any aspect of the system be it individuals, groups, resources, temperature, etc. up to and including the entire system itself. The exact question you are trying to answer will determine the object(s) you are trying to explain. For example, let’s say I am modelling fish in a small lake. There are a myriad number of questions I could ask about this system and each would have its own object. If I am asking questions on trait evolution in a certain species of fish, my object would be a specific trait (body size, colouration, etc.) within a species of fish. However, I could also ask questions about the population of each fish species. In this case my object would be all the fish in the lake. The type of question always determines what part of the system you are trying to study and it is important to recognize what part of the system you want to focus on. “Although modeling is a central component of modern science, scientific models at best are approximations of the objects and systems that they represent—they are not exact replicas. Thus, scientists constantly are working to improve and refine models.” This last part of the definition is a poignant reminder that while models are useful and can be used to explain a variety of different things, they are nevertheless approximations and can be continuously improved. Whenever designing a model, it is inherent part of the process that one must make assumptions about the system. No one can simulate every single detail of any system and because we cannot simulate every detail, we must approximate certain parts of it. The decisions about what aspects to approximate are called the model assumptions. The assumptions of any model should always be laid out plainly and cleanly so that others know the limitations of the model. This also helps up and coming modelers (and even the original modeler) know what assumptions have already been tried so they can create new models within the same system using different assumptions and compare outcomes. In this way scientist can continue to improve upon their models. So, this is Britannica’s definition of a model. Accordingly, a model is an approximation of a system used to study/explain some aspect of the system which should be employed when the system in study is difficult to experiment on and/or examine. If you have any questions about the definition feel free to contact me using the information below. Thanks, and have a great day! [1] In my experience, system is the more common term for phenomena. Most people will refer to their study system of their system of study rather than phenomena. I will be referring to the system rather than the phenomena from now on
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