Skill UI

This guide provides detailed standards for formatting empirical results (tables and figures) for the Academy of Management Journal (AMJ). It covers best practices for reporting correlation matrices, regression/SEM/HLM results, theoretical model diagrams, and interaction plots, ensuring adherence to strict academic publishing house styles (AOM house style). It helps users create self-contained, publication-ready exhibits.

A comprehensive guide for constructing conceptual exhibits—such as process models, 2x2 typologies, and multi-level frameworks—for academic manuscripts. This resource emphasizes that figures must represent pure theoretical work (constructs and relationships) rather than empirical data plots, ensuring structural clarity for top-tier academic publishing.

A guide for creating high-impact academic exhibits for literature reviews (e.g., Annual Reviews of Economics). It teaches how to synthesize findings into structured formats, including 'Who-found-what' summary tables, conceptual framework diagrams, and meta-evidence plots. The focus is on synthesizing existing knowledge across studies, not presenting original estimates. Essential for communicating complex, cross-field research findings to non-specialists.

This guide provides detailed instructions on designing high-quality visual exhibits for academic literature reviews, such as the Annual Review of Sociology (ARSoc). It covers three primary exhibit types: 'Who-found-what' summary tables, conceptual framework figures, and meta-evidence plots. The focus is on synthesizing findings across multiple studies and structuring arguments, rather than presenting new primary estimates or raw data.

A comprehensive guide for structuring and refining exhibits (tables and figures) for high-level academic journals. It provides best practices for both qualitative data (e.g., data-to-theory tables, process models) and quantitative data (e.g., cumulative regression, interaction plots), ensuring that the visual presentation strengthens the core argument. Focuses on self-contained, rigorously formatted, and interpretable scholarly communication.

This guide outlines best practices for designing and executing Computer Aided Verification (CAV) empirical evaluations. It emphasizes ensuring evidence matches claims by using standard, pinned benchmark sets, selecting fair baselines, respecting equal resource limits, and employing rigorous reporting methods like cactus and scatter plots to establish technical soundness and performance.

A comprehensive guide for creating publication-quality scientific figures, adhering to high-impact journal standards. Covers critical topics such as optimal sizing for print widths, displaying underlying raw data (dot plots, replicates), ensuring colorblind accessibility, structuring stand-alone legends, and maintaining image integrity. Essential reading for researchers preparing manuscripts.

A comprehensive guide for finalizing empirical tables and figures for high-level academic journals. It mandates moving beyond mere statistical significance by requiring deep economic interpretation (magnitude analysis). Covers three-line table conventions, proper event-study plot construction (CI and time markers), and precise variable sourcing (formula and database name) to ensure publication readiness.

A detailed guide for authors submitting theoretical machine learning papers (like COLT) regarding the appropriate inclusion and design of numerical simulations. It emphasizes that numerics should only visualize proved bounds, phase transitions, or separations, maintaining the focus on theoretical proofs rather than empirical data. Provides rules for plotting, reporting variability, and maintaining academic honesty.

A comprehensive guide for creating rigorous, self-contained, and scientifically accurate tables and figures for academic manuscripts, particularly in the field of criminology. It details best practices for visualizing complex statistical results, including age-crime curves, trajectory plots, survival analyses, and spatial hot-spot maps. The focus is on ensuring evidence is clear, reproducible, and communicates the research findings effectively to expert reviewers.

Provides stringent guidelines for formatting tables and figures in high-level economics and finance manuscripts. Covers mandatory three-line table styles, column count limits, rigorous variable definition requirements (including naming specific databases), data source transparency, and professional figure generation techniques (e.g., 300 dpi, proper event study plots).

Provides detailed guidelines for developing tables and figures in Developmental Psychology manuscripts, adhering to APA 7th edition standards. Focuses on making developmental change explicit by using age/time on the x-axis, plotting individual trajectories (spaghetti plots), and displaying model-implied mean curves with confidence intervals, moving beyond simple group mean comparisons.