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Equation 21 · A Chatbot Confessed to Being Built by a Company That Never Trained It

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c∈{V,H}c\in\{V,H\}

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cc

Symbol c

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VV

Symbol V

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HH

Symbol H

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Define the channel-attributable transfer rate for exposure class c∈\in\{V,H\} as TcT_c=Iˉc−I01−I0\frac{\bar I_c-I_0}{1-I_0} . This is a direct borrowing from the attributable-risk fraction used in outbreak epidemiology, where it measures what share of disease in an exposed group would disappear if the exposure were removed; here it measures what share of a model’s trait incidence would disappear if its exposure to the source artifact were removed, holding everything else about the model constant. TcT_c=0 means the exposed class shows the trait no more often than baseline: no signal. TcT_c=1 means every trait-negative case in the exposed class would have been positive under full exposure: the strongest…
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Define the channel-attributable transfer rate for exposure class c∈\in\{V,H\} as TcT_c=Iˉc−I01−I0\frac{\bar I_c-I_0}{1-I_0} . This is a direct borrowing from the attributable-risk fraction used in outbreak epidemiology, where it measures what share of disease in an exposed group would disappear if the exposure were removed; here it measures what share of a model’s trait incidence would disappear if its exposure to the source artifact were removed, holding everything else about the model constant. TcT_c=0 means the exposed class shows the trait no more often than baseline: no signal. TcT_c=1 means every trait-negative case in the exposed class would have been positive under full exposure: the strongest possible signal. TcT_c is dimensionless and bounded in [-1,1] ; a negative value, exposure suppressing the trait relative to baseline, is possible and would itself need explaining.

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