The phrase -- Survival of the fittest -- brings a tone as if THE FIT is hacking/destroying/ killing/removing everyone else who are not so fit. But lets take a look at the flip side -- contrarian approach. This phrase may actually bring a tone of co-operation /help/creation.
For argument's sake, let us assume Lion to be THE FITTEST. Highest in the food chain, Lion can kill/remove everyone below him. In such a scenario, there will be no one left to destroy which will lead to the destruction of THE FITTEST. But the evidence is otherwise.
Dawkins wrote in his book that in a race between a wolf and rabbit, rabbit should win more often (LESS FIT guy) because wolf is just running for dinner while rabbit is running for life. This fact shows that evolution may not mean a particular species getting better but it may mean that the whole ecosystem is improving. If wolf were to improve to run fast (through many generations) rabbit should also improve to run faster else it would become extinct or vice-versa.
Hence, improvement in one entity should lead to improvement in other. It appears that nature has devised certain laws which will make entities co-operate even though we might think otherwise. In the ecosystem of Tennis players, Roger Federer evolved at the fittest. In the Australian open, what all of us noticed was that others are also evolving to the level of Federer, the whole tennis ecosystem has improved over the past few years. The balance in the ecosystem will not let on entity fly out to far. This has happened because the aim of every player is to beat Federer and so he will try to learn from Federer. In effect, the FITTEST is teaching less FIT how to reach his level (not directly but other players are watching Federer's videos).
Tennis ecosystem is not valid for many general scenarios because guys compete to win and they can't really co-operate. But we can look at other ecosystems (work, community, family) where THE FITTEST, if co-operate with less fit, will increase the level of ecosystem involved.
Confusing !!! Read about Iterated Prisoner's dilemma.
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