make q.scoreplot based on zsc, not zsc_n

[maxheld83]

as became evident in fixing #293, the difference between zsc_n and zsc can actually be quite large.

Consider this example:

> keyneson$before$zsc_n[c("wealth-tax", "land-value-tax-resources", "poor-central-planner", "exchange-value"), ]
#$                         resentment critical moderate
#$ wealth-tax                       -7       -1       -1
#$ land-value-tax-resources         -2       -2       -2
#$ poor-central-planner              1       -1        5
#$ exchange-value                    5       -3        0
> keyneson$before$zsc[c("wealth-tax", "land-value-tax-resources", "poor-central-planner"), ]
#$                         resentment   critical   moderate
#$ wealth-tax               -2.1678640 -0.1366178 -0.3485350
#$ land-value-tax-resources -0.4351152 -0.5700473 -0.6622631
#$ poor-central-planner      0.5499858 -0.4273613  1.4859067

Here, looking at zsc_n, the item poor-central-planner, looking from resentment, appears to be quite assymmetrically distinguishing, with a difference of -2 and 4, respectively. However, when looking at the original zsc, we see that in fact, the qdc diff is quite symmetrical.

I was stumped by this in double-checking the qdc lines (which are based on zsc), though this is of course a bigger issue that relates to all zsc_n.

zsc_n naturally implies a loss of information, though troublingly, a particular kind: it will (typically) enforce a kind of spread that's not really there in the factor scores.

Of course, if zsc_n and its plots are strictly interpreted as ordinal data, there's no problem: it is correct.

We must be careful however not to interpret the horizontal dim as distance, which it is not.

Obviously, the other big problem here is that a continuous kind of plot would lead to horrendous overplotting.

[maxheld83]

Here we go.

Pretty close to the standard plot that @aiorazabala build, but some extra bells and whistles.

I find the interpretation to be harder than q.scoreplot(), probably because the text is harder to read / relate to the data, but there's now way around that (overplotting).