Tables & Figures (govern-tables-figures)
In a Governance paper the exhibits are where a comparative reviewer checks whether the institutional
claim actually travels. A single-country result dressed up as a wall of coefficients reads as
parochial; a clean cross-national table or a coefficient plot that shows where the effect holds and
where it does not reads as a contribution to how the state governs. With a working cap of ≤ 9,000
words excluding citations/bibliography (检索于 2026-06；以官网为准), every exhibit must earn its place,
and the heavy robustness grids belong in the supplementary file, not the article.
When to trigger
- Designing the main results table/figure or the key descriptive comparative exhibit
- Showing cross-country / cross-institution variation (a map, a small-multiples panel, a forest plot)
- Deciding what stays in the article vs. moves to supplementary material
- A reviewer found an exhibit unclear, single-country-parochial, or not self-contained
Principles
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Self-contained. A reader understands each exhibit from its caption, column/axis labels, and note
alone — units, sample, time window, country/case set, N, and what the estimate is. State the
estimand, not just "Model 3."
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Make the comparison visible. The point of a Governance exhibit is usually the contrast across
countries, regimes, policy domains, or institutional types. Order rows/panels by the institutional
logic (e.g., by state capacity, by Westminster vs. consensus), not alphabetically, so the pattern
reads off the page.
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Figures over dense tables for effects. Coefficient/forest plots, marginal-effects and
predicted-probability plots, and event-study plots communicate magnitude and uncertainty better than
a coefficient dump. Always show intervals, never stars alone.
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Three-line regression tables. Booktabs style — top rule, header rule, bottom rule, no vertical
rules. SEs in parentheses under coefficients; report N, the FE/clustering structure, and the
estimator; define every abbreviation in the note.
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Accessible. Colorblind-safe palette, legible in grayscale, no chartjunk, no 3D. Distinguish
series by shape/linetype as well as color so the print and the PDF both work.
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Reproducible. Each exhibit is generated by the master script; the printed numbers match the
replication materials cited in the Data Availability Statement exactly (see
govern-transparency-and-data).
Comparative-governance exhibit menu
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Cross-national descriptive table — countries/cases in rows, institutional variables in columns;
group by regime type or region; flag missing data honestly rather than blanking cells.
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Coefficient / forest plot — one estimate per country or per institutional subgroup with CIs;
ideal for showing where a mechanism holds and where scope conditions bite.
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Event-study plot — for a reform or a staggered policy adoption across units; pre-trend periods on
the left of zero, effect periods on the right, reference period marked.
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Maps — for geographic or cross-country variation (subnational governance, diffusion of a reform);
use a sequential colorblind-safe ramp, classed not continuous, with the breaks justified in the note.
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Small multiples — one panel per country/case showing the same relationship; the comparison is the
argument.
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Case / process exhibits — for qualitative or comparative-historical work: timelines, sequence
diagrams, and evidence tables linking each claim to its source (pairs with QDR-style documentation).
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. Governance is public administration and institutions research — comparative and causal designs on governance reforms; the chain serves its quantitative-causal lane, while comparative-historical / qualitative work uses its own standards.
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Tables:
etable (multi-model columns) or did_summary_to_latex straight from the
result_id.
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Figures:
plot_from_result / enhanced_event_study_plot / event_study_table —
axis units and the SE/clustering note baked in.
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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.
Checklist
Anti-patterns
- A wall of country coefficients with no plot showing where the effect travels and where it stops
- Tables that require the prose to be intelligible (not self-contained)
- Significance stars with no effect size or confidence interval
- Alphabetical country ordering that hides the institutional pattern the paper is about
- Color-only encoding that collapses in grayscale or for colorblind readers
- Cramming every robustness check into the main text and blowing the 9,000-word cap
- Exhibit values that do not match the deposited replication output
Output format
【Main exhibit】what it shows + why this form (table/plot/map)
【Comparison visible?】cross-country/institutional contrast reads off the page? [Y/N]
【Self-contained?】caption + labels + note + units/N/case-set present? [Y/N]
【Accessible?】grayscale-legible + colorblind-safe? [Y/N]
【Article vs supplementary】split decided; 9,000-word impact noted
【Reproducible?】generated by master script, matches materials? [Y/N]
【Next】govern-writing-style
Supplementary resources
