Consider $\mathcal{F}$ and $\mathcal{G}$ are two continuous distributions and that $\mathcal{G}$ is more dispersed than $\mathcal{F}$ in the sense of satisfying:
$$(1)\quad F^{-1}(\beta)-F^{-1}(\alpha)\leq G^{-1}(\beta)-G^{-1}(\alpha),\quad \forall 0< \alpha < \beta <1.$$
Then, we know (Kochar (2012), eq. 2.16) that (1) is equivalent to
$$(2)\quad\frac{F^\prime(x)}{G^\prime G^{-1}F(x)}\geq 1.$$ (I call the left hand side of (2) the Doksum ratio after (Doksum 1969))
Now consider the ratio:
$$(3)\quad\gamma(\mathcal{F},\mathcal{G})=\underset{x:F^\prime(x)>0}{\min}\;\frac{F^\prime(x)}{G^\prime G^{-1}F(x)}$$
For many distributions I find that, for fixed $\mathcal{F}$, $\gamma(\mathcal{F},\mathcal{G})$ can be made arbitrary large by shifting/rescaling $\mathcal{G}$.
For example, for the normal, student t, Weibull, gamma I find that $\gamma(\mathcal{F},\mathcal{G})$ is an increasing function of $\text{Var}(\mathcal{G})$.
My question is this: Is it always so that for fixed $\mathcal{F}$, $\gamma(\mathcal{F},\mathcal{G})$ can be made arbitrarily large by re-scaling/shifting $\mathcal{G}$?