has what I was looking for. It’s less Dawkins’ meme and more gestalt. In a sense, they can be seen as equivalent of course.
I’d say my way of thinking is a little more https://en.wikipedia.org/wiki/Transactional_analysis Transactional Analysis, although not strictly so.
You’ve got the stereotypical behavior patterns, which would be TA and maybe Dawkins yet gestalt has more of an ethos – the “inbetween bits”, which can also be transferred.
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you’re also right in that a lot of what I said is conjecture. But in neuroscience, listening to the same music can cause nearly identical brainwave patterns and also self-reporting.
I should mention that I don’t think it’s identical. I don’t think it CAN be. Too much complexity between two different brains. Even identical twins are unique.
But I think it’s important to notice patterns.
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“just”
It’s more powerful than a just. Consider the https://en.wikipedia.org/wiki/Combinatorics .
Consider the brain a very large but finite structure.
Consider the number of “caught” memes.
Consider how many ways they can be chopped up, recombined, abstracted, connected, with or without conscious consideration as your mind is making meaning.
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Ok, I skipped a few steps. That’s fair.
Consider the analogy or the metaphor. With them, you can connect a diverse set of physical and conceptual “objects”. You can also connect a diverse set of “actions”, “relationships” and “descriptions”.
Now, each meme as a concept can be described in a sentence form. Through analogy or metaphor, it can be connected to a far ranging set of other concepts.
The original meme is subsumed and the novel analogy or metaphor, as a new construct, becomes useful in its own right and can be connected to further analogies or metaphors.
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All true. Ultimately, we are all unique.
My usual bias is to emphasize that.
However, there is value in analyzing patterns.
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[set of all possible metaphors or analogies a meme can transform into] — that could theoretically be countable.
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Example I can (and I have, once long ago] write a poetry engine.
(I wrote it in Turbo Pascal because it was handy – sorry)
Markov chain with a parts-of-speech dictionary basically.
It was crude but worked. If it creates a novel image in your mind, then you know it works.
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