Introductory models & basic concepts: fidelity of transmission

Fidelity

Shannon and Weaver were concerned to eliminate 'noise', meaning factors which decrease the quality of reception of the message. Although they were mainly concerned with physical noise in the channel, they also used the term in a broader sense. In communication theory, the term 'noise' is often refers to any interfering factor at any stage of the process of communication. Shannon and Weaver used the term semantic noise to refer to the Transmitter's mode of address and that term, (often in a wider sense, since it should be notes that Shannon was not concerned with meaning) is still used. In essence, how to avoid semantic noise is what the practical application of communication studies is all about.

The ideal communication act would be one where the information transmitted is received exactly as it was sent, in other words received with total fidelity. The word 'fidelity' is used here in the same way as it is used in the term 'hi-fi(delity)'. As an example, suppose that a computer randomly generates XDHJITES and sends those characters down a 'phone line to another computer. If the second computer then displays XDHJITES on its screen, fidelity of reception can be said to be perfect.

In communication in the everyday, messy world, of course, fidelity is not generally so high. (In fact, if you use computers much, you'll be aware that it's rarely perfect in information technology either!) How often have you upset somebody without intending to, failed to upset somebody when you did intend to, misinterpreted instructions for assembling a flat-pack wardrobe, misunderstood a map, overlooked a road sign, agreed to something you really wanted to object to etc? None of us would have any difficulty finding examples of low fidelity in communication and many of them would have nothing to do with simple physical noise.

Pause for a moment now and think of a couple of recent examples of low fidelity in communication and see if you can think of reasons for that low fidelity. For instance, you recently asked a teacher for help with something you found difficult, but were none the wiser after her explanation. Why?

David Berlo's S-M-C-R Model can give us some clues...