Beyond the molar-molecular distinction: we need multiscaled analyses.

Hineline (2001) wrote a theory paper about avoidance. The author said we should stop picking sides between molar and molecular views.

Instead, we need to look at both time scales at once. The paper used avoidance as the main example.

The paper found that neither molar nor molecular views alone explain avoidance. Both scales matter.

Choosing one scale over the other hides important data. We need multiscaled analyses.

Warburg (2001) published the same year but took the opposite stance. That paper claimed molar is superior. This looks like a clash, yet both agree the old either-or debate is broken.

Baum (2002) followed a year later and pushed the molar-only view even harder. It acts like a successor, trying to move the field toward molar and away from N's multiscale idea.

Shimp (2020) finally gave us a way to do what N asked. It offers a clear method: plot 10-s counts next to session totals. This extends N's call into everyday practice.

Next time you graph data, show both the minute-by-minute line and the session average bar. If the two stories differ, you have found the multiscale signal N wants us to see. This simple step keeps you from missing local spikes that smooth totals hide, and it stops you from chasing tiny blips that vanish in the big picture.