Skill UI

A comprehensive guide to understanding the Public Opinion Quarterly (POQ) peer review process. It helps researchers critically assess their manuscripts against high academic standards, including double-blind review protocols, rigorous survey methodology checks (Total Survey Error, AAPOR compliance), and anticipating reviewer demands for code and data. Use this skill to stress-test your paper's robustness and maximize its chances of successful publication.

A comprehensive checklist and guide for authors preparing manuscripts for scholarly submission, specifically for Public Opinion Quarterly (POQ) via ScholarOne. It ensures compliance with double-blind anonymity, specific word count caps, mandatory AAPOR disclosure elements (Appendix A), and proper data archiving protocols (Dataverse). Use this guide as the final critical check before clicking 'Submit'.

This guide details the rigorous methodology for conducting systematic literature reviews and meta-science pieces, particularly for integrative reviews in psychology (PoPS style). It instructs researchers on how to systematically gather evidence across multiple sub-areas by utilizing techniques like forward/backward snowballing, comprehensive database sweeps (e.g., PsycINFO), and developing detailed evidence matrices. The focus is on synthesizing findings and establishing replicable search protocols to ensure academic rigor and comprehensiveness, moving beyond simple summarization.

A comprehensive guide detailing the open science and reproducibility standards required for academic publications, especially those utilizing original data or conducting meta-science. It outlines critical steps such as data repository deposit, protocol preregistration, and reporting inter-rater reliability to ensure research methods are fully auditable.

This skill guides the planning of psychological studies to meet the highest academic standards. It provides comprehensive methodologies for performing power analysis, justifying sample sizes, and implementing preregistration protocols. Use this when initiating a new research project or developing a pre-analysis plan to ensure the study design is robust and transparent.

This skill details the rigorous methodology for defining study eligibility criteria and coding data for comprehensive meta-analyses. It emphasizes pre-specifying inclusion/exclusion rules in a protocol, developing a detailed codebook, performing double-coding, and calculating inter-rater reliability (e.g., Kappa, ICC) to ensure the reproducibility and trustworthiness of synthesis findings.

This skill guides authors in assembling a comprehensive transparency package for academic submissions (especially meta-analyses). It ensures adherence to Open Science principles by detailing requirements for protocol preregistration (PROSPERO/OSF), depositing the coded database, codebook, and analysis scripts. It is essential for proving the full reproducibility of quantitative research findings.

A structured guide for authors responding to major revisions or reject-and-resubmit decisions from high-stakes academic journals like QJE. This process outlines a rigorous protocol for triaging reviewer comments, prioritizing editor mandates, structuring the point-by-point response letter, and ensuring the manuscript is fully updated before submission. It focuses on maintaining a professional, gracious, and evidence-based tone.

A comprehensive preflight checklist designed for authors submitting to the Quarterly Journal of Economics (QJE). This guide ensures manuscripts comply with strict academic standards, including single-PDF formatting, double-blind anonymization protocols, and correct author-date referencing, saving time and improving submission quality.

A comprehensive guide detailing best practices for achieving high reproducibility in recommender system research. It covers critical areas such as dataset version pinning, defining symmetric tuning protocols, selecting full-ranking metrics, handling non-determinism via multiple seeds, and structuring rigorous divergence analysis for academic publications.

A comprehensive guide for revising academic papers in recommendation systems (RecSys). It covers best practices for structuring the first page, ensuring rigorous evaluation protocols (e.g., temporal splits, equal-budget baselines), and avoiding methodological overclaims, helping authors meet the standards of top-tier AI conferences.

A comprehensive guide for developing a rigorous, a-priori protocol for systematic reviews and meta-analyses in educational research. This tool ensures methodological transparency by defining the scope (PICO), eligibility criteria, search strategies, screening procedures, and synthesis plans before any data is collected, protecting the integrity of the research findings.