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It is not the case that The claim's sharp threshold language thus misrepresents a gradient of fixation probabilities as a binary bifurcation point.
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Reasons For
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Reason for
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1.
Mathematical modeling often requires threshold definitions for practical analysis; binaries can be useful simplifications without being false.
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2.
Biological systems themselves may exhibit near-threshold behavior where fixation appears functionally binary despite underlying gradients.
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3.
The claim assumes precision language is always epistemically superior, but context-dependent approximations serve legitimate explanatory purposes.
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Reasons Against
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Reason against
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1.
Fixation probabilities in population genetics vary continuously with mutation rates, selection coefficients, and population size parameters.
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2.
Binary language ('fixed' vs 'unfixed') obscures intermediate states where alleles have measurably different but non-absolute persistence likelihoods.
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3.
Misrepresenting gradients as thresholds can lead to false predictions about evolutionary outcomes in real biological systems.
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