A good model isn't a description, it's an explanation. An accumulation of observations does not explain anything.
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What is the difference between an “explicative” and a “descriptive” model, precisely?
Gravity (without gravitons) is a description of how this works, not an explanation, but it’s a damn good model.Just read the thread. A description says "given this input, we observed this output" ("given this search query, we get these results"). An explication provides the model that produces the output (e.g. PageRank algorithm) and thus generalizes to arbitrary inputs.
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Saying "it doesn't answer why" is a tautology. There is no why in science, only how. Why is used to describe human intent.
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