Last year I gave a number of talks on a new model of the relationship between communication and research, which I have covered in “Ghosts, models and meaning in science,” and a more detailed text, here. I’ll be adding articles on this theme in the coming weeks. Comments are greatly appreciated – they have already significantly improved the project.
The core point is that scientific messages derive meaning from their relationship to various models and other concepts that often remain “invisible” (ghosts) in a given text or communicative context. This is true of all kinds of communication, of course. But the natural sciences relate meaning to models in specific, highly structured ways that can be recovered. If this invisible architecture is not shared by a writer or speaker, meaning will be lost. A failure to take this into account is one of the most common reasons people misunderstand a message. And in doing science, being unaware of the link between a project and the models that spawned it can become an obstacle to generating new hypotheses or fully understanding what happens in an experiment.
The inherent connection between thinking about, doing and communicating science is crucial to the quality of research and has important implications for science education. Here I present two slides I use in my talks. These “Concept maps” expose some of the patterns that link these ideas.
The first slide shows how a very specific scientific question (rose-colored box at the bottom) can be fit into a hierarchy of more general questions and models. There is no single path for creating such a chart: the same question at the bottom could be analyzed upward in different ways. You might diagram it within a more chemical or physical or evolutionary pathway, because specific questions are embedded in all kinds of models.
There are several important implications.
First, at some level, an experiment which seeks an answer to a very specific question also challenges the higher-order models it is embedded in. Basically, an experiment may be shaking a big tree and probing assumptions concerning several levels of the hierarchy and how they are linked. A highly specific experiment can refute a very large model, theory or linked set of assumptions. For example, all kinds of simple experiments might have shaken evolutionary theory, or a study that characterizes tumor samples could overturn a view of how a particular therapy works.
Secondly, an audience may know nothing about the example given below, which involves NF-kB, transcription factors, signaling pathways and so on. When trying to explain something, a scientist needs to make a reasonable guess about the knowledge of an audience and the kinds of things they are interested in, then find the right level of the hierarchy to jump in. Going downward provides a logical path for a dialogue that moves from a general question to a more specific one – and how they fit together.
The second slide links the way this communicative strategy can help scientists think about a problem more clearly, see relationships between models, and widen their understanding of the implications of their work.
Stay tuned for more soon.