The original theory was precisely that there's a general factor ("g").

If you run anything sufficiently complex through a principal component analysis you'll get several orthogonal factors, decreasing in importance. The question then is whether the first factor dominates or not.

My understanding is that it does, with "g" explaining some 50% of the variance, and the various smaller "s" factors maybe 5% to 20% at most.