Skill UI

A comprehensive guide for designing conceptual figures for highly theoretical manuscripts (e.g., Psychological Review). This skill teaches how to create two types of non-experimental exhibits: structured model/architecture diagrams and simulation-of-model-behavior plots. It emphasizes rigorous academic standards, including defining constructs vs. processes, distinguishing predictions from fits, and ensuring figures are self-contained and diagnostic.

A guide for articulating the unique theoretical advancement of a psychological review manuscript. It instructs authors on how to frame their findings using the 'before $\rightarrow$ after' structure, defining what the field can explain after the paper that it could not previously, and critically identifying the specific prior models improved upon.

A specialized methodology for theoretically placing a new model within an existing academic conversation. It instructs the user to build a 'rival map' by identifying diagnostic phenomena, contrasting them with established rival theories, and explicitly stating where the new theory excels, surpasses, or subsumes existing claims. This approach moves beyond simple literature review to active theoretical confrontation.

This guide provides best practices for positioning a scholarly manuscript within the field of public administration. It instructs authors on how to elevate their niche contributions into field-wide debates, ensuring the paper speaks to both academic scholars and practicing managers. It emphasizes linking theory gaps to practical policy stakes.

This guide teaches authors how to properly position their research contribution within a specialized academic field, particularly for journals like Research Policy. It instructs users on how to move beyond simple citation lists by identifying a clear, theoretical knowledge gap (a tension) in the existing literature. By anchoring the work in foundational canons and naming the prevailing consensus, authors can structure a compelling argument that defines what the field should believe after reading the paper.

This guide helps researchers precisely define the marginal contribution (the 'delta') of their academic work. Instead of writing a general literature tour, it instructs authors to compare their findings directly against 3-5 most proximate prior papers, emphasizing specific advancements in identification or measurement. It is crucial for submissions to high-stakes journals.

A comprehensive guide for executing rigorous empirical accounting studies. This resource details best practices for advanced econometric techniques, including correct standard error clustering (firm-level, two-way clustering), executing identification strategies (DiD, RD, IV/2SLS), validating accounting constructs, and performing extensive robustness checks (falsification, placebo tests). It also emphasizes data provenance and reproducibility, critical for top-tier academic publications.

A comprehensive guide for establishing credible causal inference in accounting and finance research. This methodology covers advanced techniques including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity (RDD), and experimental design. It instructs users on how to move beyond simple controls, defining the specific identifying variation necessary for publishing rigorous, causality-focused academic work.

This comprehensive guide provides a rigorous framework for scientific reporting, ensuring statistical integrity and full reproducibility. It instructs authors on essential elements like reporting effect sizes, justifying sample sizes, controlling for multiple comparisons, and distinguishing biological from technical replicates, helping manuscripts meet the high standards of top-tier scientific journals.

This guide outlines the rigorous standards required for submitting top-tier academic papers, such as those for ACM SIGCOMM. It instructs authors on how to transition from general claims to highly evidence-based arguments by focusing on measured operational pain, defining design principles, and pairing every performance claim with concrete testbed, trace, or deployment evidence. Essential for researchers in networking and systems.

A comprehensive guide for positioning a paper for ACM SoCC. It instructs authors to write the related work section by bridging both systems literature (e.g., OSDI, NSDI) and data-management literature (e.g., SIGMOD, VLDB). Focus must be on stating the 'delta'—the unique difference—rather than merely listing citations, ensuring dual anonymity and covering all relevant technical lanes.

This guide provides a structured framework for academics to elevate their research topics. It instructs authors on transforming narrow empirical questions into major theoretical and institutional debates, connecting research to core societal issues (China, World, Era). It emphasizes moving beyond simple policy assessment to address structural contradictions and theoretical gaps, suitable for advanced academic writing.