Measurement, Temporal Distance, and The Hierarchical Taxonomy of Purple
Gist: This post is a musing on whether the ‘factor structure’ we find for psychological constructs like emotion is just an artifact of the temporal scale we use to measure them. I’m using the analogy of a Japanese Maple tree: from a distance, it’s a single “purple” factor, but up close, it resolves into many distinct color factors. The idea is that our measurement intervals—moment, day, month—are just different temporal distances, each revealing a different, but equally ‘true’, view of a person’s inner world. It makes me cautious about mixing scales.
I’ve been turning over an idea that I can’t seem to shake. It’s about measurement, and how the timescale we choose to measure with might fundamentally change the psychological phenomena we think we’re observing. It feels almost obvious when I write it down, but the implications seem to ripple out in interesting ways.
The core of it is this: as our measurement interval gets longer—moving from a moment, to a day, to a week—what we’re measuring seems to shift from something discrete and flickering to something more stable and “trait-like.” I wonder if this means that the number of “factors” we find in our data isn’t just a property of the person, but an artifact of the temporal lens we’re using to look at them.
The Japanese Maple from a Distance
I keep coming back to a visual analogy. Imagine looking at a Japanese Maple tree from 200 yards away. From that distance, the canopy might resolve into a single, dominant color. If I were to “factor analyze” the colors of that tree from afar, I’d likely find a one-factor solution: “Purple.” All the colors would load heavily onto this single dimension. It’s a true representation of the tree from that distance.
But what happens if I walk 100 yards closer? Now, my perception has a higher resolution. I can distinguish the bright orange leaves on the sunny side from the deeper violet hues in the shade. My one-factor “Purple” model breaks down. I now have at least two factors: “Orange” and “Violet.”
If I walk right up to the tree and stand beneath its branches, the complexity multiplies. I can see that some leaves are a brilliant, almost-neon red. Others have yellow edges. Some of the “violet” leaves I saw from a distance are actually a deep, subtle blue mixed with purple. Suddenly, my two-factor model is insufficient. I might now need five factors to adequately describe the colors: Red, Orange, Yellow, Blue, and Purple.
None of these factor solutions are “wrong.” They are all accurate representations of the tree at different observational distances. The number of factors, the “structure” of the color, is a function of my proximity.
The Distant Self and the Momentary Self
This is where the idea gets interesting for me when thinking about affect. What if time is just another kind of distance?
When we ask someone to fill out a questionnaire about their “past month,” we are, in a sense, asking them to view their “distant self.” From that temporal distance, the fine-grained details of their emotional life may blur. The momentary flashes of pride, joy, and excitement that occurred over thousands of moments might blend together in memory’s calculus. When they reflect, they may only be able to access the broad strokes, the overarching impression. It wouldn’t surprise me if their experience, when measured this way, resolves into just two dominant “colors”: a “Positive Affect” factor and a “Negative Affect” factor.
But what if we measure their “daily self”? Here, we’re a bit closer. The resolution is higher. They might be able to distinguish “anxious” feelings from general “sadness,” or “contentment” from “excitement.” More factors might emerge because the temporal distance is shorter, and less mental averaging is required.
And then there’s the “momentary self,” the target of things like Ecological Momentary Assessment (EMA). This is our attempt to stand right under the branches of the tree. Here, we might expect to see the most complexity, the greatest number of distinct affective “factors.” Yet, even here, I have my doubts. Is EMA truly measuring a single, instantaneous emotional state? Or is it asking someone to pause and perform a rapid “mental calculus” of the last 60 seconds? Even our most granular measurements might still be a slight time-average, a small bundle of experiences rather than a single, discrete emotional leaf.
Some Wrinkles in the Analogy
This line of thinking makes me cautious. If the factor structure of affect is dependent on the temporal scale of measurement, then what does it mean to mix those scales? It seems akin to trying to run a single analysis on a photograph of the whole tree from 200 yards away and a microscopic image of a single leaf’s cell structure. The data are measuring phenomena at such fundamentally different levels of organization that asking how they “group” together feels like a category error.
It also makes me question what a “factor” even is in this context. Perhaps, at a given timescale, a factor doesn’t represent some deep, underlying latent entity. Maybe it simply tells us which discrete emotional states are most likely to be bundled together or co-occur within that specific temporal window. The “Positive Affect” factor in a weekly survey might not be a singular entity, but simply a name we give to the observation that moments of joy, interest, and contentment tended to happen in close succession during that period.
I don’t have an answer here. It’s just a thought experiment. But it does seem that the “truth” of our inner world’s structure might not be a single, static architecture. Perhaps it’s more like that Japanese Maple—a different, but equally valid, truth revealed at every possible distance from which we choose to look.