Skill UI

A structured guide on translating behavioral or game-theoretic arguments into pre-specified, quantitative, and testable hypotheses for Experimental Economics (ExpEcon) manuscripts. This methodology emphasizes moving beyond informal intuition by defining the experimental game, deriving benchmark predictions, layering competing behavioral accounts, and generating comparative-statics hypotheses that treatments must adjudicate. It is essential for manuscripts aiming to robustly test theory through design.

This guide helps researchers structure their economic questions for top experimental economics journals. It emphasizes framing the contribution around a novel, clean experimental design (the 'minimal pair') and the treatment effect, rather than merely the topic itself. It guides authors on decision-making regarding experimental types, pre-registration, and selecting the appropriate academic venue.

This router guides researchers through the systematic process of preparing a manuscript for Experimental Economics (ExpEcon), the ESA's flagship journal. It identifies the correct specialized skills (e.g., theory modeling, robustness checks, referee strategy, rebuttal) needed at each stage, ensuring adherence to methodological rigor, including incentive compatibility and the no-deception norm. It is designed to help teams structure their research from initial design to final submission.

This comprehensive guide provides structural and stylistic advice for authors submitting experimental economics manuscripts. It emphasizes adopting a 'design-forward' narrative, ensuring procedural transparency, quantifying results in subjects' units, and meticulously structuring the core design section to meet the high standards of expert reviewers.

This tool guides authors through the rigorous standards required for publishing in top experimental economics journals. It serves as a comprehensive checklist, evaluating a manuscript's fit, methodological strength, design transparency, and structural requirements (e.g., pre-registration, incentive-compatibility) against best practices in behavioral and experimental economics.

This guide outlines the rigorous methodological standards for empirical work in AI fairness, accountability, and transparency (FAccT). It advises researchers on matching specific claims (e.g., disparate harm) to appropriate evidence types—including disaggregated metrics, coded qualitative data, and documented ethical procedures. It stresses the importance of ethical review, handling protected attributes, and acknowledging limitations to ensure high scientific and ethical rigor.

This guide provides a comprehensive model of the academic review process used at FAccT. It details the interdisciplinary nature of the review panel (CS, law, social science), the OpenReview workflow, and the strategic implications of the 'Accept/Revise/Reject' decision set. It guides authors on navigating the stages, including rebuttals and revise-and-resubmissions.

A comprehensive audit guide for submitting academic papers to the FAccT conference. It details critical, multi-step processes, including the mandatory abstract registration gate, maintaining mutual anonymity, adhering to strict ACM formatting rules, and including required endmatter statements (such as the Generative AI Usage Statement).

A comprehensive guide for authors submitting to FAccT, detailing the mandatory separation of content into three zones: the main Body, the Endmatter statements (including Ethics and AI Usage), and the Appendix/Supplementary material. It outlines strict rules regarding anonymity, page limits, and ensuring the core argument is decision-critical and visible from the main reviewed pages.

A comprehensive project management guide for submitting interdisciplinary, responsible AI papers to major academic conferences like FAccT. It provides a detailed backward-planning timeline, covering milestones from initial abstract registration and literature review to revisions, camera-ready submission, and conference presentation, emphasizing ethical considerations and structured academic processes.

A comprehensive guide for authors preparing a USENIX FAST camera-ready version. It details all necessary post-acceptance steps, including complete de-anonymization, applying the official two-column template, integrating required revisions, and permanently archiving all artifacts with DOIs to meet strict publication deadlines.

This guide provides comprehensive best practices for writing the 'Related Work' section for submissions to top-tier storage conferences like FAST. It emphasizes adopting a 'delta-first' contrast approach, requiring authors to position their novelty against the entire spectrum of storage literature (including OSDI, SOSP, and dedicated workshops), rather than merely citing proximate works. It also covers handling concurrent submissions and maintaining double-blind anonymity.