Skills Data Science Conceptual Exhibits for Theoretical Models

Conceptual Exhibits for Theoretical Models

v20260724
psychrev-conceptual-exhibits
A comprehensive guide for designing conceptual figures for highly theoretical manuscripts (e.g., Psychological Review). This skill teaches how to create two types of non-experimental exhibits: structured model/architecture diagrams and simulation-of-model-behavior plots. It emphasizes rigorous academic standards, including defining constructs vs. processes, distinguishing predictions from fits, and ensuring figures are self-contained and diagnostic.
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Overview

Conceptual Exhibits: Model Diagrams & Simulation Figures (psychrev-conceptual-exhibits)

When to trigger

  • The theory is built and derived; now it must be shown
  • Your figure is boxes-and-arrows with no specified dynamics
  • You have a model but no plot of what it does
  • A reviewer will ask "show me the model's behavior, not just its architecture"

The two figure types Psychological Review actually uses

Figures here carry theoretical work. They are almost never plots of an experiment you ran (you ran none). There are two legitimate kinds:

  1. Model / architecture diagrams — the structure of the theory: components, representations, information flow, feedback. Every box is a defined construct or module; every arrow is a specified process or relationship from the theory, not decoration.
  2. Simulation-of-model-behavior figures — the model's output: predicted curves, surfaces, phase portraits, parameter sweeps, fits to existing data. This is the figure that does the persuasive work — it shows the model produces (or fails to produce) the diagnostic phenomena.

A third, supporting kind: model-vs-data and model-vs-rival overlays, where the model's prediction is plotted against published data points or against a rival model's prediction.

Design rules for model diagrams

  • Every box maps to a named assumption/construct/module in the text; every arrow to a specified process. If a reader cannot read the diagram off the model description, it is decoration.
  • Distinguish core structure from implementational detail visually (e.g., shading), so reviewers see what is load-bearing.
  • Keep the level of analysis consistent within a diagram (do not mix computational and implementational components without saying so).
  • Label representations and processes with the same terms used in the equations/algorithm.

Design rules for simulation figures

  • Plot the diagnostic behaviors — the patterns that distinguish your theory from rivals.
  • State, in the caption, the parameters used and whether they were fit or set a priori; a simulation figure with undisclosed parameters is unreviewable.
  • Show parameter sweeps where the qualitative pattern is the prediction (the pattern should be robust across the plotted range, per psychrev-boundary-conditions).
  • Overlay existing data when confronting the model with evidence; cite the data source.
  • When comparing to a rival, plot both predictions on the same axes; do not compare across panels with different scales.
  • Mark which curves are predictions (model not tuned on them) vs. fits (tuned).

Caption discipline (APA)

A Psychological Review caption is self-contained: what the panel shows, the model and parameters that produced it, the data source if overlaid, and what theoretical point it makes. Numbering and labels must match the text exactly; reference every figure in the prose.

Checklist

  • Every model-diagram box is a defined construct/module; every arrow a specified process
  • Core structure is visually distinguished from implementational detail
  • At least one simulation figure shows the model's diagnostic behavior
  • Simulation captions disclose parameters and whether they were fit or set a priori
  • Predictions (untuned) are visually distinguished from fits (tuned)
  • Model-vs-data and model-vs-rival overlays share axes and cite data sources
  • Figures meet APA resolution/format specs; numbering and labels match the text

Anti-patterns

  • A box-and-arrow diagram that cannot be read off the model description (decoration)
  • Presenting the architecture but never the behavior the architecture produces
  • Simulation figures with undisclosed or cherry-picked parameters
  • Comparing model and rival across panels with mismatched axes/scales
  • Plotting a fit and implying it is a prediction
  • A figure of an experiment — there is no experiment; data appear only to constrain the model

Output format

【Figure list】[Fig 1: diagram | Fig 2..n: simulation/behavior | overlays vs. data/rival]
【Diagram check】boxes=constructs, arrows=processes, core vs. impl. distinguished: yes / fix
【Behavior figures】diagnostic patterns shown; parameters disclosed (fit vs. a priori): yes / fix
【Predictions vs. fits】visually marked: yes / fix
【Captions】self-contained, APA, matched to text: yes / fix
【Next step】psychrev-contribution-framing → psychrev-writing-style
Info
Category Data Science
Name psychrev-conceptual-exhibits
Version v20260724
Size 4.76KB
Updated At 2026-07-29
Language