Crim Tables Figures

Tables & Figures (crim-tables-figures)

Exhibits are where an expert reviewer checks whether the crime result is real. Criminology has its own signature figures — the age–crime curve, trajectory-group plots, survival curves, and crime maps — and each 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. an online appendix/supplement
• A reviewer found an exhibit unclear, mislabeled, or non-self-contained
• Presenting a trajectory model, survival analysis, or spatial pattern

Principles

1. Self-contained. A reader should understand each exhibit from its title, axis/column labels, and note alone. State the crime measure, units (counts vs. rates per 100k), sample, N, and time window.
2. Figures over dense tables for effects. Coefficient/forest plots, predicted counts/rate-ratio plots, and marginal-effects plots beat a wall of coefficients. Always show intervals.
3. Show the curve, not just the coefficient. Age–crime curves, trajectory-group plots (with group shares and CIs), and Kaplan–Meier / cumulative-incidence recidivism curves communicate the criminological story directly.
4. Maps when place is the point. Hot-spot / kernel-density / choropleth maps for spatial variation; label the unit (block, tract, agency) and the rate denominator; avoid misleading raw-count maps.
5. Accessible. Colorblind-safe palettes; legible in grayscale; no chartjunk or 3D. Reviewers parse fast.
6. Reproducible. Each exhibit is generated by the master script; numbers match the deposited package exactly (see crim-data-and-transparency).

Criminology-specific exhibits

• Trajectory plots: show group shares, posterior-probability summary, and CIs — not just mean lines.
• Survival/recidivism: report at-risk counts, censoring, and competing risks where relevant.
• For qualitative work: timelines, life-history charts, evidence tables linking claims to sources.

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. Criminology is observational — place/person panels where selection is pervasive; foreground DiD/IV/RDD and the selection objection.

• 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

• Maps or tables of raw crime counts where rates are needed (population not held constant)
• Trajectory plots that hide group shares or classification quality
• Reporting significance stars with no effect size or interval
• Cramming every robustness check into the main text instead of a supplement
• Exhibit numbers/values that don't match the deposited code output

Exhibit choice for the signature crime objects (decision table)

Each criminology figure carries a known probe; pick the exhibit that answers it.

Worked micro-example: fixing a misleading hot-spot map (illustrative)

A draft maps raw burglary counts and the downtown tract glows red. A referee reads it as a risk claim it does not support — downtown has 5x the nighttime population (illustrative). The fix: switch to a rate per 1,000 ambient population, use a colorblind-safe sequential palette, label the unit and denominator in the note, and move the raw-count version to the supplement. Now the exhibit shows concentration of risk, the object the routine-activity argument claims.

Exhibit pass for Criminology

Treat this skill as an executable review pass, not a prose hint. First lock the crime/justice process, measurement validity, research design, and policy consequence; then judge whether the current manuscript answers the venue's real reader: criminology reviewers who expect theory-linked crime, justice, or harm mechanisms plus transparent measurement.

• Do the pass: For every table or figure, state the estimand or object, sample or case base, uncertainty display, and one sentence the exhibit proves for the venue audience.
• Return a ledger: give claim / evidence / risk / manuscript location rows, so the next agent can edit rather than rediscover the issue.
• Sibling guard: compare against Justice Quarterly for applied justice, Journal of Quantitative Criminology for methods focus, Social Problems for broader sociological framing; if a sibling owns the contribution, recommend re-routing before polishing format.
• Stop condition: do not give submission-ready advice until the pack's resources/official-source-map.md has been checked for volatile rules and the manuscript has one concrete fix for the largest venue-specific risk.

Output format

【Main exhibit】what it shows + why a figure/table/map
【Crime metric】counts vs. rates + denominator stated? [Y/N]
【Self-contained?】title + labels + note + N/units/time present? [Y/N]
【Accessible?】grayscale-legible + colorblind-safe? [Y/N]
【Main text vs supplement】split decided
【Reproducible?】generated by master script, matches package? [Y/N]
【Next】crim-writing-style

Supplementary resources

• ../../resources/external_tools.md — plotting, mapping, trajectory, and survival packages
• ../../resources/official-source-map.md — formatting and double-spacing expectations

Source: brycewang-stanford/Awesome-Journal-Skills → Criminology-Skills/skills/crim-tables-figures/SKILL.md