메뉴
SkillsMP는 nealcaren/social-data-analysis에서 17개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 17개 중 17개를 표시합니다.
Simulate peer review by constructing reviewer personas from Zotero sources. Identifies relevant perspectives, retrieves full texts, builds reviewer profiles, and generates focused reviews on theory/methods and findings.
원문 언어: 영어
Draft publication-ready Theory sections for sociology research. Guides structure, paragraph functions, sentence craft, and calibration based on analysis of 80 Social Problems/Social Forces articles.
원문 언어: 영어
Meta-skill for creating genre-analysis-based writing skills. Analyzes a corpus of article sections, discovers clusters, and generates complete skills with phases, cluster guides, and techniques.
원문 언어: 영어
Draft case justification sections for interview-based sociology articles. Guides cluster selection, component coverage, and calibration based on analysis of 32 Social Problems/Social Forces articles.
원문 언어: 영어
Orchestrate manuscript revision by routing feedback to specialized writing skills
원문 언어: 영어
Draft publication-ready Methods sections for interview-based sociology articles. Guides pathway selection, component coverage, and calibration based on analysis of 77 Social Problems/Social Forces articles.
원문 언어: 영어
Write article introductions and conclusions for sociology interview research. Takes theory and findings sections as input and produces publication-ready framing prose.
원문 언어: 영어
Build systematic literature databases for sociology research using OpenAlex API. Guides you through search, screening, snowballing, annotation, and synthesis with structured user interaction at each stage.
원문 언어: 영어
Deep reading and synthesis of literature corpus. Theoretical mapping, thematic clustering, and debate identification using Zotero MCP for full-text access.
원문 언어: 영어
Pragmatic qualitative analysis for interview data in sociology research. Guides you through systematic coding, interpretation, and synthesis with quality checkpoints. Supports theory-informed (Track A) or data-first (Track B) approaches.
원문 언어: 영어
Write-up support for qualitative interview research in sociology. Guides methods and findings drafting with emphasis on argument-driven narrative, not formulaic quote display.
원문 언어: 영어
Develop causal diagrams (DAGs) from social-science research questions and literature, then render publication-ready figures using Mermaid, R, or Python.
원문 언어: 영어
Abductive analysis for qualitative interview data following Timmermans & Tavory. Guides you through theory-first analysis that recognizes anomalies and generates novel theoretical insights through systematic puzzle exploration.
원문 언어: 영어
Transform textbook chapters into engaging, evidence-based lectures with Google Slides. Guides instructors through learning outcomes, narrative design, active learning activities, and slide creation via Google Docs MCP.
원문 언어: 영어
R statistical analysis for publication-ready sociology research. Guides you through phased workflows for DiD, IV, matching, panel methods, and more. Use when doing quantitative analysis in R for academic papers.
원문 언어: 영어
Stata statistical analysis for publication-ready sociology research. Guides you through phased workflows for DiD, IV, matching, panel methods, and more. Use when doing quantitative analysis in Stata for academic papers.
원문 언어: 영어
Computational text analysis for sociology research using R or Python. Guides you through topic models, sentiment analysis, classification, and embeddings with systematic validation. Supports both traditional (LDA, STM) and neural (BERT, BERTopic) methods.
원문 언어: 영어