Skill UI

A comprehensive guide for authors submitting to Sociological Methods & Research (SMR). It routes authors through the rigorous, multi-stage process required for publication, covering methodological contribution, derivation, simulation studies, empirical illustration, and ensuring full software reproducibility. This tool helps authors structure their manuscript to meet high academic standards.

This guide helps researchers determine the ideal venue for their cloud computing research paper. It outlines the architectural boundaries between pure systems (OSDI/SOSP), pure data management (SIGMOD/VLDB), and the systems-data intersection (SoCC). It provides crucial tests, such as the model-swap and re-label tests, and advises on necessary evidence maturity (measurement studies, experience papers) to ensure a high chance of acceptance.

A comprehensive guide for applying advanced quantitative methods (OLS, Multilevel, Survival Analysis) to large-scale social surveys (CGSS, CFPS, etc.). This guide emphasizes shifting the focus from purely statistical identification (econometric coefficient races) to deep sociological interpretation, focusing on revealing social mechanisms, structural heterogeneity, and real-world social consequences.

A comprehensive guide for executing and reporting complex social psychological analyses required for expert peer review. This skill covers norms for reporting uncertainty, assessing measurement quality, ensuring robustness checks, selecting appropriate statistical inference (e.g., multilevel models, clustering), and linking statistical findings back to the theoretical structure. It emphasizes methodological rigor and reproducibility.

A comprehensive guide for authors preparing manuscripts for Social Psychology Quarterly (SPQ). It ensures that all tables and figures are self-contained, highly accessible, and correctly formatted according to the ASA Style Guide. The focus is on clearly communicating the 'structure–individual link' and presenting complex statistical results to a mixed sociology/psychology readership.

A comprehensive guide for authors submitting to SCI journals, detailing best practices for making research code and data available. It addresses how to proactively provide reproducible materials, structured documentation, and honest availability statements, even when formal 'Artifact Evaluation' badges are not mandatory. It helps authors improve the robustness and impact of their scientific findings.

A comprehensive guide for researchers submitting academic papers, detailing the standards required for scientific reproducibility. It covers fixing experimental environments (toolchains, datasets, hardware), differentiating result sources (simulation vs. physical measurement), statistical reporting best practices, and providing clear guidelines for code and data availability statements.

A comprehensive guide for authors submitting technical papers, detailing methods to ensure that all reported claims, figures, and benchmark numbers can be independently regenerated. This involves creating VM-ready, self-contained artifacts, mapping every claim to a specific script, and defining clear reproducibility levels (Turnkey, Scripted) to satisfy conference requirements.

A comprehensive guide for conducting and reporting rigorous empirical analysis in academic research, particularly in finance and accounting. It covers selecting appropriate estimators (e.g., DiD, 2SLS, RDD), handling fixed effects, ensuring statistical robustness through placebo and alternative testing, and fulfilling strict data-authenticity and code-access requirements required by top-tier journals.

A comprehensive methodological guide for designing rigorous academic studies in accounting. It details advanced econometric techniques—including Difference-in-Differences (DiD), Instrumental Variables (IV), Regression Discontinuity Design (RDD), and experimental setups—to establish credible causal identification. Use this guide when your research challenge is solving endogeneity or isolating a specific economic channel from complex, non-random variables.

This skill details the rigorous process of converting raw statistical outputs into self-contained, publication-ready tables and figures for top-tier academic journals. It ensures compliance with strict house styles, covering sample selection, descriptive statistics, main regression results, and specific formatting for DiD, RDD, and event studies, all while adhering to strict page limits and providing economic magnitude interpretation.

This skill guides authors on positioning information retrieval (IR) work for the Text REtrieval Conference (TREC). It functions as a venue-selection and manuscript re-framing tool, ensuring the submission aligns with TREC's focus on shared evaluation tracks, test collections, and NIST-style benchmarking. It helps authors structure evidence, understand reviewer expectations, and distinguish the work from general CS conference submissions.