Tables & Figures (asr-tables-figures)

Exhibits are where a masked reviewer checks whether the result is real. ASR excludes tables and figures from the 15,000-word limit (text, references, and footnotes count) — so you are not penalized for a clear exhibit, but it must earn its place and stand on its own.

When to trigger

• Designing the main results table/figure or a key descriptive exhibit
• Deciding what belongs in the article vs. supplementary materials
• A reviewer found an exhibit unclear, mislabeled, or not self-contained
• Presenting qualitative or comparative-historical evidence in tabular/visual form

Principles

1. Self-contained. Title, row/column labels, and a complete note make each exhibit intelligible alone. State the sample, N, units, weighting, and what the estimate is.
2. Show magnitude and uncertainty. Effect sizes and intervals — not stars alone. Coefficient and marginal-effects plots often beat dense coefficient walls.
3. Sociology-specific exhibits. Mobility/transition tables and flow diagrams; survival curves and Lexis/age-period-cohort surfaces for demography; network graphs; sequence-analysis chronograms; evidence tables linking claims to sources for comparative-historical/ethnographic work.
4. Accessible. Colorblind-safe palettes; legible in grayscale; no chartjunk or 3D.
5. Reproducible. Generated by the master script (quantitative) so numbers match shared materials; for qualitative exhibits, excerpts must be faithful to the coded data.

Format

• Follow the ASA Style Guide for table/figure formatting and notes.
• Double-spaced manuscript, Times New Roman 12 pt; place tables/figures per the guidelines.
• Keep identifying information out of exhibits (masked review).

Exhibit conventions a masked ASR reviewer expects

The ASA flagship admits exhibits from every tradition but holds them to one standard: a reviewer who may not share your method must be able to read the evidence unaided. Match the exhibit to the tradition, then verify it carries magnitude and uncertainty.

Worked micro-example (illustrative)

A main results table for an administrative-data study of gender wage gaps is redesigned for ASR.

Before: 6 columns of coefficients, stars only, no note → reviewer can't tell magnitude or sample
After: marginal-effects plot — adjusted gap 14.2% (95% CI 11.8–16.6), N=412,000, survey-weighted,
  occupation + firm FE; grayscale-legible, colorblind-safe palette
Self-contained note (illustrative): "Predicted gap from a weighted model; bars are 95% CIs;
  estimates reproduce from master.R, seed=11."

The redesign makes the exhibit stand alone, leads with the substantive magnitude an inequality scholar cares about, and ties the numbers to the shared script.

Referee pushback → ASR-specific fix

• "I can't read this table without the text." → Add a complete note (sample, N, units, weighting, what the estimate is) so it is intelligible alone.
• "Stars don't tell me if this matters." → Replace with effect sizes and intervals, ideally a marginal-effects plot a generalist can scan.
• "Your figure dies in grayscale." → Re-encode with colorblind-safe, grayscale-legible channels; drop chartjunk and 3D.
• "The qualitative table looks cherry-picked." → Include contrary excerpts and report the coding scheme so the evidence reads as systematic.

Calibration anchors

• Exhibits are excluded from the word cap — use the room. ASR counts text, references, and footnotes but not tables/figures, so a clear, self-contained exhibit costs nothing against length.
• Magnitude over significance. The flagship's broad readership wants to know how much, with what uncertainty, not merely that a coefficient cleared a threshold.
• One reproducibility standard, two forms. Quantitative values must match the master script; qualitative excerpts must be faithful to the coded data — both are checkable claims to a reviewer.

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers (the usual source of body-vs-supplement drift). Full map: execution-with-mcp. ASR is general sociology where observational designs dominate; foreground identification (DiD/IV/RDD), decomposition, and clustered inference.

• Tables: etable (multi-model columns) or did_summary_to_latex straight from the result_id.
• Figures: plot_from_result / enhanced_event_study_plot / event_study_table — axis units and the SE/clustering note baked in.
• Every note names the estimator + clustering and states the effect size in interpretable units.

See a full fitted-result → exhibit chain in the JF execution walkthrough.

Anti-patterns

• Tables that require the prose to be intelligible (not self-contained)
• Significance stars with no effect size or interval
• Decorative figures that add no evidence
• Color-only encoding that fails in grayscale or for colorblind readers
• Quantitative exhibit values that don't match the analysis script

Output format

【Main exhibit】what it shows + why a table/figure
【Self-contained?】title + labels + note + N/units/weights present? [Y/N]
【Magnitude + uncertainty shown?】[Y/N]
【Accessible?】grayscale-legible + colorblind-safe? [Y/N]
【Reproducible / faithful?】matches script or coded data? [Y/N]
【Next】asr-writing-style

Supplementary resources

• ../../resources/external_tools.md — plotting, demography, and network visualization tools
• ../../resources/official-source-map.md — word-count rule (tables/figures excluded) and ASA Style Guide