Skill UI

This guide outlines the strategic allocation of content—such as results, methods, and limitations—into the main body, appendix, or artifact for academic submissions. The core principle is 'decision-criticality': any information a reviewer must read to accept the paper must reside in the main body, ensuring key findings are not hidden in supplementary materials or repositories.

This tool guides researchers in selecting and rigorously stress-testing appropriate methodologies (quantitative, qualitative, or normative) for public administration manuscripts. It ensures methodological alignment with the core research question, providing detailed checks for causal inference techniques (DID, IV, RDD) and qualitative rigor, thereby strengthening the overall academic argument.

This guide assists researchers in transforming academic findings into highly actionable and evidence-based policy recommendations. It specifically addresses the standards required for top-tier journals in public administration, emphasizing the mandatory link between observed 'Discovery' and proposed 'Suggestion' via an underlying 'Mechanism.' It teaches how to avoid generic filler language and structure policy suggestions around specific actors, stages, and concrete actions.

A specialized tool designed to guide authors in drafting professional and structured rebuttal letters for academic journals, particularly those in Public Administration. It provides detailed templates and guidance for addressing reviewer comments, focusing specifically on strengthening theoretical frameworks and justifying methodological fits to meet high academic standards.

This skill provides rigorous standards and best practices for running and reporting analyses within Comparative Political Studies (CPS). It addresses common pitfalls in cross-national data, such as measurement error, few clusters, and spurious correlation, ensuring the resulting research is transparent, robust, and replication-ready for academic review.

This guide provides a comprehensive methodological framework and checklist for researchers conducting quasi-experimental and micro-panel studies in rural economics. It systematically addresses common econometric pitfalls, such as self-selection bias, reverse causality, and endogeneity, detailing best practices for advanced methods like Difference-in-Differences (DID), Instrumental Variables (IV), Regression Discontinuity (RDD), and Propensity Score Matching (PSM).

A comprehensive guide for rigorous data analysis execution and reporting in criminology research. This skill covers advanced econometric techniques required for analyzing complex crime data, including count models (Negative Binomial, Zero-Inflated), fixed-effects panel data, and survival/recidivism modeling. It emphasizes transparently reporting uncertainty, addressing selection bias, and ensuring methods are fully reproducible for expert peer review.

This skill guides authors through defending complex research designs in Criminology. It covers advanced quantitative methods (e.g., DiD, IV, RDD, fixed effects), longitudinal analyses, and qualitative case studies. It teaches how to establish causal identification, address selection bias, and argue against rival theories, ensuring methodological rigor for high-impact academic submissions.

A comprehensive guide for designing and auditing empirical research in CSCW. It emphasizes methodological pluralism, defining distinct standards of rigor for various techniques like ethnography, trace analysis, surveys, and mixed methods. The guide mandates pre-design planning, explicitly addressing ethical concerns, unit of analysis, and aggregation logic before data collection.

This guide details best practices for enhancing the credibility of academic manuscripts submitted to scholarly journals, particularly addressing code and data availability. It teaches authors how to proactively provide stable links, checksums, comprehensive reproducibility scripts, and clear licensing statements. The focus is on bolstering trustworthiness for single-blind review processes, even when the journal does not mandate formal artifact badges.

This guide provides a systematic framework for authors preparing revision response letters and revision explanations for academic journals. It covers essential strategies for handling major vs. minor revisions, structuring point-by-point responses, addressing conflicting opinions, and ensuring all changes are accurately documented. Ideal for authors aiming to successfully resubmit a manuscript.

This guide provides an expert framework for advanced econometric analysis, focusing on establishing causal inference in fields like finance and trade. It details best practices for quasi-experimental designs (DID, IV, RDD, DML) and rigorously addresses common endogeneity issues such as policy bias, reverse causality, and anticipation effects, ensuring robust research methodology.