Skill UI

This skill provides a rigorous framework for defending the methodology of advanced educational research manuscripts, suitable for top-tier academic journals. It guides users through defining research structure across quantitative (e.g., multilevel, quasi-experimental), qualitative (e.g., ethnography, case study), and mixed methods paradigms. Focus areas include addressing rival explanations, ensuring measurement validity, establishing causal claims, and meeting stringent reporting standards (AERA).

This guide outlines the strict transparency and data availability requirements for manuscripts submitted to the American Educational Research Journal (AERJ). It ensures adherence to AERA standards for reporting empirical social science research (both quantitative and qualitative) and the AERA Code of Ethics. It details how authors must make findings reproducible, whether by providing code and data access paths, or by documenting an inspectable analytic trail.

This skill helps authors determine if their research, which focuses on the complex interface between agricultural management and environmental outcomes, is appropriate for the journal 'Agriculture, Ecosystems & Environment.' It details the required scope, from greenhouse gas fluxes and biodiversity to soil and water quality at the field-to-landscape scale, emphasizing the necessity of environmental outcome quantification and sound ecological methodology.

This guide provides detailed standards for planning, auditing, and executing data analysis for sociological manuscripts, specifically tailored to the standards of the American Journal of Sociology (AJS). It stresses that analysis must credibly support a theoretical claim, rather than simply showcasing technical proficiency. Key areas covered include quantitative robustness checks, comparative-historical logic, ethnographic procedure, and the crucial principle of triangulation across diverse data sources.

A comprehensive guide for authors submitting to the American Journal of Sociology (AJS). It outlines best practices for data documentation, ensuring research provenance, and ethically sharing findings in both quantitative and ethnographic contexts. It emphasizes creating a thorough, checkable evidentiary trail appropriate to the claim, while clarifying AJS's non-mandatory policy on replication deposits and adherence to confidentiality standards.

A comprehensive guide for structuring and defending the methodological design of social science manuscripts, particularly for high-impact journals like AJS. It covers diverse traditions—including quantitative, comparative-historical, ethnographic, and network analysis—ensuring the design rigorously supports the theoretical claim, rather than just presenting data. Use this when justifying case selection, identifying assumptions, or linking field observations to major theoretical arguments.

This guide helps pure-mathematics researchers precisely state and frame the main theorems of their manuscripts for submission to top-tier journals. It emphasizes techniques for quantifying novelty, separating the core headline result from corollaries, and rigorously positioning the work relative to the existing state of the art, mimicking the structure of Annals of Mathematics submissions.

A specialized tool for polishing pure mathematics manuscripts, designed to enhance the rigor and overall flow of academic writing. It guides authors to eliminate soft language (e.g., "clearly," "obviously"), ensure precise quantification, explicitly state constant dependencies, and structure hypotheses meticulously. Ideal for late-stage proof refinement before journal submission.

A comprehensive guide for conducting rigorous analysis for Accounting, Organizations, and Society (AOS) manuscripts. It covers both qualitative methods—such as coding, building evidence chains, and weighing counter-evidence—and quantitative techniques, including experimental, survey, and archival model estimation. The focus is on maintaining a fully reproducible audit trail and reconciling mixed-methods findings.

This guide helps researchers determine if their empirical economic manuscript is suitable for submission to AEJ: Economic Policy. It focuses on transforming a clean empirical finding into a policy-driven narrative by identifying a concrete policy lever, stating a clear policy question, and quantifying the welfare or cost-benefit implications.

This guide outlines the rigorous execution and reporting standards required for quantitative research intended for top-tier academic journals, such as APSR. It covers best practices for ensuring reproducibility, assessing robustness, reporting uncertainty honestly (using credible intervals), and correctly applying advanced statistical inference (e.g., clustering, randomization inference). It is essential for researchers conducting empirical work in political science, economics, or social sciences.

This guide assists researchers in strengthening the methodological rigor of academic work, particularly in political science. It provides structured methods for defending research design, covering rigorous causal identification for quantitative work (e.g., DiD, IV, RDD) and systematic case selection/process tracing for qualitative analysis. Use this when facing reviewer skepticism or preparing a pre-analysis plan to ensure the evidence credibly connects to the theoretical argument.