Is maximizing hamming distance the same as minimizing correlation? For the design of an error correcting code, I might wish to maximize the distance between the codewords $\sum a_i \oplus b_i$.

For spreading sequences I'd like to minimize the cross-correlation at $t=0$ of $\sum \sigma(a_i)\sigma(b_i)$ where $\sigma(\cdot)$ maps binary $0\to1$ and $1 \to (-1)$ (i.e. what you'd get out of a BPSK matched filter when $E_b$ is normalized and there is no noise).

Are these criteria the same? It seems to me that since $\sigma$ acts as an isomorphism that turns cyclic$\pmod 2$ addition into cyclic complex multiplication, they are equivalent statements. Can you verify this and let me know where I can read more about it?
Two codewords $c_1$ and $c_2$ of length $n$, with elements in $\lbrace +1, -1 \rbrace$, and Hamming distance $d$, have a cross-correlation given by $$(n-d) -d = n-2d.$$ The reason is that there are $n-d$ bits that are equal and their product is $1$, and $d$ bits that are different and their product is $-1$.

Note that:


The larger the distance $d$, the smaller the correlation.
The correlation by itself does not tell you anything about the distance, since you also need to know $n$. For example, $1,1,1$ and $-1,-1,-1$ have correlation $-3$ but $1,1,1,1,1,1$ and $1,1,1,-1,-1,-1$ have correlation $0$.