Skill UI

This guide helps researchers meet rigorous open science and transparency requirements, such as those mandated by journals like JAP. It details the process of depositing data, analysis code, and materials with persistent identifiers (DOIs), drafting comprehensive data-availability statements, and correctly managing prior-use disclosures and pre-registrations. Essential for ensuring research reproducibility and publication compliance.

This skill guides the execution and reporting norms for advanced data analysis in communication studies, specifically adhering to the rigorous standards of the Journal of Communication (JoC). It emphasizes transparency, reproducibility, honest reporting of uncertainty (beyond p-values), rigorous robustness checks, and proper handling of computational data, ensuring that analyses withstand expert and peer review.

This guide provides a rigorous structural and strategic framework for responding to a 'Revise and Resubmit' (R&R) decision, specifically tailored for the Journal of Labor Economics (JOLE). It emphasizes drafting concise, point-by-point rebuttals, addressing complex identification challenges with robust diagnostics, reconciling conflicting referee demands, and strictly adhering to the journal's word economy and single-blind submission rules. It is a critical tool for refining advanced academic manuscripts.

This skill provides detailed guidance on assessing a research paper's alignment with the scope of quantitative economics and technical economics journals. It helps determine if the core contribution lies in advanced quantitative methods, econometrics, efficiency measurements (TFP, DEA), or input-output analysis, guiding authors toward the most suitable academic publication venue.

This guide helps polish academic manuscripts for high-impact policy journals (like JPAM). It focuses on achieving a clear, calibrated, and decision-oriented voice. Learn how to state policy implications without overclaiming, ensuring the findings are legible to a cross-disciplinary audience of economists, public policy scholars, and practitioners. It emphasizes matching claims to the actual statistical design and stating necessary scope conditions.

This guide outlines the rigorous open science and transparency requirements for submissions to the Journal of Personality and Social Psychology (JPSP). It details compliance with APA's TOP Guidelines at Level 2, mandating the proper disclosure of data, analysis code, and materials in a trusted repository. It also covers JARS reporting standards and guides authors on stating the preregistration status, ensuring research reproducibility.

This guide provides comprehensive methodology for advanced empirical analysis in Public Economics, particularly for manuscripts using large administrative or register microdata. It covers advanced topics like estimating behavioral elasticities, calculating welfare metrics (MVPF, DWL), and ensuring robust causal identification strategies. It emphasizes translating raw coefficients into policy-relevant quantities with rigorous uncertainty quantification.

This guide provides expert editorial standards for structuring tables and figures in public economics manuscripts, specifically tailored for submissions to the Journal of Public Economics. It emphasizes making the policy design visible by leading with graphical evidence (such as bunching plots, RD, or event-studies) rather than relying solely on regression coefficients, thereby enhancing credibility with specialized referees.

This guide provides rigorous structural and stylistic guidelines for academic manuscripts in the field of risk and uncertainty. It instructs authors on how to precisely articulate decision models, quantify results with appropriate magnitude and precision, and structure arguments (Abstract, Introduction, Exposition) to meet the high standards of specialized journals, ensuring technical honesty and clarity.

A comprehensive pre-writing guide for researchers determining the optimal venue and track for a data science contribution. It outlines a two-stage decision process: first, assessing if the work aligns with the KDD focus on data regimes (scale, drift, heterogeneity); and second, selecting the correct track (Research, ADS, Datasets & Benchmarks, etc.) based on the strongest, most honest evidence available—especially emphasizing real-world deployment outcomes.

Provides detailed guidelines for creating high-standard clinical figures and tables, modeled after leading medical journals (e.g., The Lancet). It covers essential display items including Table 1 (baseline characteristics), Kaplan-Meier survival curves (with numbers-at-risk), Forest plots for meta-analyses, CONSORT/PRISMA flow diagrams, and global maps. The guide emphasizes the rigorous reporting of 95% confidence intervals (CIs) and proper statistical methods to ensure scientific accuracy.

This guide provides comprehensive guidelines for authors preparing linguistic manuscripts, focusing on data documentation, reproducibility, and ethical sharing practices. It details how to properly share quantitative data, elicited fieldwork corpora, and phonetic measurements while adhering strictly to community consent, licensing terms, and best academic practices. It emphasizes that transparency must be coupled with ethical responsibility.