Is the first derivative of
$Pr(x)=\frac{e^{\beta_0+\beta_i x_i}}{1+e^{\beta_0+\beta_i x_i}}$
a Gaussian function?
Is the first derivative of
$Pr(x)=\frac{e^{\beta_0+\beta_i x_i}}{1+e^{\beta_0+\beta_i x_i}}$
a Gaussian function?
The short answer is NO. (Differentiating cannot introduce an $x^2$ term in the exponential.)
Longer answer: Out of curiosity I just differentiated the (almost trivial) case $\beta_0 = 0$, $\beta_1 = 1$, because this claim was made in another question here recently.
The derivative is $e^x/ (1 + e^x)^2 $. Note that this is symmetric about zero. Thus, if it is equal to some Gaussian $\frac{1}{\sigma \sqrt{2 \pi}} e^{ (x - \mu)^2/2\sigma^2 }$ then the mean is necessarily $\mu = 0$. Moreover, for the functions to agree when $x = 0$, we must have $\sigma \sqrt{2 \pi} = 4$.
Thus, the only possible Gaussian would have $\mu = 0$, $\sigma = 4/\sqrt{2 \pi}$. This is plotted below. The differing behaviour is clear. (Admittedly they are a better match than I imagined though).

curve( dnorm(x, sd= 4/sqrt(2 * pi)), xlim=c(-7,7), col = "red" )
curve( exp(x)/ ( (1 + exp(x))^2 ), add=T )