Sozialwissenschaftliche Forschungsassistenten

Natur- und Sozialwissenschaften · Berufliche Fähigkeiten & Kompetenzen · SOC 19-4061 · 309 Skills

Beruflicher Kontext

Diese O*NET-Aufgaben beschreiben den Beruf und geben Kontext für die SOC-Zuordnung. Sie bedeuten nicht, dass jeder aufgeführte Skill jede Aufgabe erfüllt.

Design and create special programs for tasks such as statistical analysis and data entry and cleaning.
Provide assistance with the preparation of project-related reports, manuscripts, and presentations.
Prepare tables, graphs, fact sheets, and written reports summarizing research results.

Die O*NET-Aufgaben werden in ihrer Ausgangssprache (Englisch) angezeigt. Die Aufgabendaten sind der O*NET® 29.1 Database der USDOL/ETA entnommen und werden gemäß CC BY 4.0 verwendet.

Repräsentative Quellen

Eine begrenzte Auswahl beliebter, diesem Beruf zugeordneter Skills, mit höchstens einem Skill je GitHub-Repository. Darunter folgt die vollständige Zuordnung.

persona-researcher

googleworkspace/cli

Organize research — manage references, notes, and collaboration.

figure-composer

companion-inc/feynman

Compose a publication-grade multi-panel scientific figure from a claim, dataset, or draft result. Use when the task needs panel planning, consistent figure layout, figure review, or final figure assembly.

brycewang-stanford/Auto-Empirical-Research-Skills

E1-Quantitative Analysis Guide with Code Generation & Sensitivity Analysis VS-Enhanced with Full 5-Phase process: Avoids obvious analyses, explores innovative methodologies Expanded to include qualitative analysis (thematic, grounded theory, content, narrative) Absorbed E4 (Analysis Code Generator) and E5 (Sensitivity Analysis - Primary Study) capabilities Use when: selecting statistical/qualitative methods, interpreting results, checking assumptions, generating code, sensitivity analysis Triggers: statistical analysis, ANOVA, regression, t-test, power analysis, assumption checking, effect size, thematic analysis, grounded theory, content analysis, narrative analysis, NVivo, ATLAS.ti, coding, qualitative data, R code, Python code, SPSS syntax, sensitivity analysis, robustness check

Alle zugeordneten Skills

Durchsuchen Sie die vollständige Zuordnung nach Repository-Beliebtheit oder jüngster Quellaktivität.

Namen und Beschreibungen der Skills bleiben in der vom Quell-Repository bereitgestellten Sprache.

Sortieren nach

persona-researcher

googleworkspace/cli

Organize research — manage references, notes, and collaboration.

figure-composer

companion-inc/feynman

Compose a publication-grade multi-panel scientific figure from a claim, dataset, or draft result. Use when the task needs panel planning, consistent figure layout, figure review, or final figure assembly.

companion-inc/feynman

Apply scientific plotting and figure-quality rules to a single plot or panel. Use when drawing, cleaning, labeling, or reviewing plots for research artifacts.

brycewang-stanford/Auto-Empirical-Research-Skills

E1-Quantitative Analysis Guide with Code Generation & Sensitivity Analysis VS-Enhanced with Full 5-Phase process: Avoids obvious analyses, explores innovative methodologies Expanded to include qualitative analysis (thematic, grounded theory, content, narrative) Absorbed E4 (Analysis Code Generator) and E5 (Sensitivity Analysis - Primary Study) capabilities Use when: selecting statistical/qualitative methods, interpreting results, checking assumptions, generating code, sensitivity analysis Triggers: statistical analysis, ANOVA, regression, t-test, power analysis, assumption checking, effect size, thematic analysis, grounded theory, content analysis, narrative analysis, NVivo, ATLAS.ti, coding, qualitative data, R code, Python code, SPSS syntax, sensitivity analysis, robustness check

brycewang-stanford/Auto-Empirical-Research-Skills

Agent E2 - Qualitative Coding Specialist - Systematic coding and theme development. Covers codebook development, coding strategies, saturation assessment, and CAQDAS guidance.

brycewang-stanford/Auto-Empirical-Research-Skills

Agent E3 - Mixed Methods Integration Specialist - Qual-Quant data integration and meta-inference. Covers joint display creation, integration strategies, and legitimation techniques.

brycewang-stanford/Auto-Empirical-Research-Skills

Humanization Quality Verifier - Ensures transformation integrity and quality Validates that humanization preserves meaning, citations, and academic standards Use when: after G6 transformation, before final export, for quality assurance Triggers: verify humanization, check transformation, validate changes

brycewang-stanford/Auto-Empirical-Research-Skills

VS-Enhanced Journal Matcher with Journal Intelligence MCP — Real-time journal data pipeline with checkpoint-based human decisions. Uses OpenAlex + Crossref APIs for live metrics. Light VS applied: Avoids IF-centric recommendations + multi-dimensional matching strategy Use when: selecting target journals, planning submissions, comparing publication options Triggers: journal, submission, impact factor, academic journal, publication, submit

brycewang-stanford/Auto-Empirical-Research-Skills

Publication Specialist - Writing, Review, Pre-registration & Quality Assurance Light VS applied: Avoids template-based writing + audience-specific message design Absorbed G3 (Peer Review Strategist), G4 (Pre-registration Composer), F1-F3 (Quality functions) capabilities Use when: writing abstracts, creating summaries, peer review response, pre-registration, reporting checklists, reproducibility Triggers: abstract, plain language, press release, summary, communication, peer review, revision, pre-registration, OSF, PRISMA, CONSORT, reproducibility

brycewang-stanford/Auto-Empirical-Research-Skills

VS-Enhanced Academic Style Auditor - Academic Writing Quality Analysis Identifies 24+ writing patterns that reduce scholarly quality, adapted from Wikipedia AI Cleanup guidelines Use when: checking drafts before submission, improving academic writing quality, preparing for style improvement Triggers: writing quality, style audit, pattern check, writing review, academic style check

brycewang-stanford/Auto-Empirical-Research-Skills

VS-Enhanced Academic Style Humanizer - Transforms writing patterns to achieve authentic scholarly voice Applies transformations from G5 analysis to create natural academic prose Use when: improving AI-assisted writing quality, preparing manuscripts, enhancing scholarly voice Triggers: humanize, transform, make natural, improve writing quality, improve style

brycewang-stanford/Auto-Empirical-Research-Skills

Diverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말