asq-tables-figures

name	asq-tables-figures
description	Use when building and refining exhibits for an Administrative Science Quarterly (ASQ) manuscript — qualitative data structures and data-to-theory tables, process models, and quantitative tables. Designs exhibits; it does not run the analysis behind them.

Tables & Figures (asq-tables-figures)

When to trigger

• Your exhibits are dense, generic, or do not reveal the data structure
• Qualitative: you have quotes but no data-to-theory table or process model figure
• Quantitative: tables are over-stuffed or hide the result that matters
• Reviewers cannot reconstruct how your data became theory from the exhibits

Principle: exhibits do theoretical work

At ASQ, exhibits are part of the argument, not decoration. A reader should be able to grasp the contribution from the figures and tables alone. Build them in tandem with asq-data-analysis.

Qualitative exhibits

• Data structure figure. Show first-order codes → second-order themes → aggregate dimensions (Gioia-style), or an equivalent cross-case/process display. This is often the single most scrutinized exhibit in an inductive ASQ paper.
• Data-to-theory table. Columns: theoretical construct/dimension → representative quotes/evidence (proof quotes) → analytic note. This makes the inference auditable.
• Process model figure. For process theory, a clean phase/feedback diagram with arrows that mean something (sequence, transformation, feedback), labeled with your constructs.
• Case/site table. Comparative table of cases on key dimensions (for multiple-case designs).
• Power quotes live in the body; proof quotes live in tables — keep the body readable.

Quantitative exhibits

• Descriptives & correlations table (means, SD, correlations) — standard and complete.
• Main regression table. Build models cumulatively (baseline → controls → focal effects → interactions). Avoid wall-to-wall columns; show the models that test the theory.
• Interaction plots. Plot significant moderations; a marginal-effects/simple-slopes figure beats a coefficient alone.
• Robustness can be summarized compactly or moved to an appendix; the body shows the result that matters.

Craft standards (both)

• Each exhibit is self-contained: title, units, notes, significance conventions, and source defined in the note.
• Figures are clean and legible in grayscale; no chart-junk; consistent fonts and labels.
• Number and reference every exhibit in text; the text interprets, it does not merely repeat the table.
• Keep exhibits anonymized for ASQ's double-blind review (no author-revealing site names or acknowledgments in figure sources).
• Follow APA style for citations in notes (ASQ adopted APA in January 2025), with SAGE table conventions; manuscripts go in via ScholarOne (Word or PDF, 12-pt Times New Roman, double-spaced). Exhibits count toward length, and ASQ rewards "high intellectual value per page" — keep the whole manuscript near the suggested 35–45 pages of text (over-long files are unsubmitted before review). Verify current details at journals.sagepub.com/author-instructions/asq.

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers (the usual source of body-vs-appendix drift). Full map: execution-with-mcp. ASQ wants a clean causal or well-identified observational design behind an organizational-theory contribution; reduced-form estimation fits the chain below, interpretive work does not.

• 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.

Checklist

• Qual: data-structure figure present and faithful to the coding
• Qual: data-to-theory / evidence table lets a reader audit the inference
• Qual: process model figure (if process theory) with meaningful arrows
• Quant: descriptives + correlations table complete
• Quant: main table built cumulatively; interactions plotted
• Every exhibit is self-contained (title, notes, units, significance key)
• Text interprets exhibits rather than restating them
• Formatting matches current ASQ/SAGE guidelines (verify on official page)

Anti-patterns

• A "wall of coefficients" table where the key result is buried among dozens of columns
• Qualitative papers with quotes but no data-structure figure or evidence table
• Process figures whose arrows have no defined meaning
• Exhibits that require the body text to be interpretable (not self-contained)
• Chart-junk, illegible grayscale, inconsistent decimals/labels
• Reporting interaction coefficients without a plot

Output format

【Exhibit list】figures + tables planned
【Data-to-theory exhibit】present? (qual) / cumulative main table? (quant)
【Process model】present? (if process theory)
【Self-containment】all notes/units/keys complete?
【Formatting】matches ASQ/SAGE guidelines (verify)
【Next step】asq-writing-style