Orgstud Tables Figures

Tables & Figures (orgstud-tables-figures)

When to trigger

• Your qualitative paper has quotes scattered in prose but no data structure or evidence table
• Your process paper narrates events but has no process-model figure
• A reviewer cannot trace how your data became your constructs from the exhibits alone
• Quantitative tables are dense, asterisk-driven, or do not answer the theoretical question

Exhibits carry the auditability of the inference

At OS, the exhibits are where reviewers verify the data-to-theory inference, not where decoration goes. For qualitative and process work especially, a few well-built exhibits do more than pages of prose: they let a skeptical reader see the analytic ladder at a glance. The exhibit set is part of the rigor argument, not an afterthought.

The core qualitative/process exhibits

• Data structure figure (Gioia-style). First-order codes (informant terms) → second-order themes (researcher constructs) → aggregate dimensions. This is the single most expected exhibit in inductive OS papers; it makes the abstraction from data to theory visible in one image.
• Data-to-theory / evidence table. Rows = constructs or themes; columns = representative raw evidence (quotes, document excerpts), the code, and the construct. This is where "proof quotes" live, freeing the body for a few "power quotes."
• Process-model figure. Phases/stages with explicit transition arrows and labels — what triggers each move and what each phase accomplishes. A process model with unlabeled arrows is a common reviewer complaint; the figure must encode the mechanism, not just sequence boxes.
• Case/site comparison table. For multi-case designs (Eisenhardt idiom), a table contrasting cases on the dimensions that drive the theory.
• Informant/data-source table. Who, how many, when, role — establishing the empirical base.

Quantitative exhibits

• Descriptives + correlations with clear units; main results in interpretable form.
• Report effect magnitudes and confidence intervals, interpreted in organizational terms — not significance stars as the headline.
• Robustness in a compact appendix table keyed to the specific theoretical threat each check addresses.
• Multilevel/interaction effects plotted (marginal-effects/interaction figures) rather than left to coefficients.

Craft standards either way

• Every exhibit answers a question stated in its title/caption; if you cannot say what question it answers, cut it.
• Self-contained. Notes define abbreviations, units, sources, N; the reader should not need the body to parse the exhibit.
• The figure encodes the argument. A process figure should let a reader reconstruct the theory; a data structure should let them reconstruct the coding.
• SAGE production. Figures legible in greyscale and at print size; follow SAGE OS artwork specs at acceptance (检索于 2026-06；以官网为准).

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. Organization Studies is largely qualitative/theoretical; use the chain below only for its quantitative-empirical papers, and say so when a study is interpretive.

• 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.