Social Sci Paper Coach V7.0
Loop, Audit, Anti-Hallucination, Style Align
Description
A social science academic paper writing system integrating the AFP methodology. Core features: model essay-driven imitation loop, quad-core audit mechanism, 1500-word soft truncation, hierarchical memory loading. Supports both quantitative and qualitative social science papers, including specialized mechanisms for literature authenticity verification, data anti-hallucination, and coding analysis anti-hallucination. Ready to use out of the box. Suitable for CSSCI/SSCI journal submissions, quantitative research, qualitative research, and other high-quality social science academic paper writing and journal submissions.
Related Skills
View all
ResearchAcademic Paper Writing v4.1
A full-process academic paper writing system that combines the Five Sources model with the AFP 3.1 three-layer architecture. Other AI tools help you "write" a paper; this one helps you "plug" every hole that could get it rejected—from one vague idea to a complete submission package in a single run through seven modules, with an anti-hallucination gate, archive-code resume, and four-core review. [10-second value] One sentence of an idea → a submittable, complete paper package. Real sources are enforced throughout, every citation is verifiable, and you can resume across sessions right where you left off. [Trigger phrases] write a paper / literature review / research method design / how to write the discussion / paper polishing / abstract & keywords / submission package [Seven modules, all fully executable instructions] Phase 1 Topic & Introduction → Phase 2 Literature Review → Phase 3 Research Method Design → Phase 4 Discussion → Phase 5 Conclusion → Phase 6 Abstract & Keywords → Phase 7 Full-Text Integration & Submission Package. Phase 0 entry routes A–G map one-to-one to the seven modules, with an R option to restore your last progress via an archive code or archived document. [v4.1 upgrades] 1. Evidence-chain gate (hard constraint): a material registry (M1/M2 numbering) + four citation elements (author / year / title / verifiable locator) + three-color marking (✅ user-supplied / ⚠️ to verify / 🚫 prohibited). If the material library is empty, the system outputs only an outline and search queries and refuses to generate body text with citations; generating references from memory or fabricating volume, issue, or page numbers is forbidden. 2. Archive-code protocol: each module ends with a structured archive code that can be saved as a YouMind document. In your next session, simply reference it with @ to resume without re-requesting already locked information. 3. Reproducible scoring: the C core anchors all dimensions to behavioral standards scored at 4/6/8/10 with stated rationale; the ratchet mechanism only moves scores upward, never downward. 4. Four-discipline configuration library (1A Humanities & Arts / 1B Social Sciences / 2A Science & Engineering / 2B Agriculture, Medicine & Life Sciences), with automatic switching of theory libraries, method toolboxes, and disciplinary norms; Category 2B runs ethics review checkpoints at Phases 0, 3, and 7. 5. Three-paradigm routing (quantitative / qualitative / theoretical): literature review narrative strategies and research method design follow different paths. 6. Anti-cliché checklist and prohibitions: discussion sections using phrases like "limited time and energy" or "pending further research," conclusions introducing new data or literature, and abstracts containing claims unsupported by the body text are all sent back by the B core. 7. Adaptivity: user profile (beginner / intermediate / proficient) + paper type (journal / thesis / conference / course) + pacing mode (default / fast-forward / slow-motion) + multi-task isolation. 8. Submission package & compliance: seven consistency checks, a six-link logic chain, reference formatting (GB/T 7714 / APA 7 / Vancouver / IEEE), ethics approval number, data availability statement, generative AI use disclosure draft, and cover letter draft. [How to use] Tell the system: your discipline, target journal / paper type / word count, and which stage you're at. The system advances module by module, pausing after each one to deliver the section, review report, scorecard, and archive code, then waits for your confirmation before continuing. [Responsibility boundaries] The system handles sources 1–4 (structure, material organization, style, integration); source 5, human calibration, is yours: academic judgment, fact-checking, and innovation decisions. All ⚠️-marked citations and data must be verified by you item by item before submission; this skill does not promise any acceptance or pass outcome.
Teaching Paper Architect
From teaching research accumulation to CSSCI/SSCI/SCI — making every teaching paper stand up to peer review. This is not a tool that writes your paper for you, but a paper architect that understands educational academic norms. It knows that IMRaD is not just four letters but a rigorous argument logic; that a literature review is not a list of references but a precise positioning of research gaps; that effect sizes are more convincing to reviewers than p-values. Seven-stage full-process coverage: Topic Focus (Innovation Three-Question Check) → Literature Review (Three-Level Coding + Funnel Writing) → Research Design (Quantitative/Qualitative/Mixed Approach Decision) → Data Analysis (Statistical Method Decision Tree) → Discussion Construction (Contribution Self-Check Matrix) → Language Refinement (AI Removal + Language Elevation + Revision Notes) → Journal Adaptation (Matching Matrix + Rejection Risk Pre-Reinforcement). Built-in Triple-Core Adversarial Engine: The Academic Writer handles output, the Language Elevation Officer polishes, and the Academic Gatekeeper has veto power—are the references real? Is the data reliable? Is the argument grounded in evidence? Does the contribution match the target journal level? Five dimensions are audited item by item; if any fail, it is sent back for rework. It doesn't just help you write well, it teaches you why the changes are made—each output includes revision notes, allowing you to truly improve your academic writing skills through iterations. Supports bilingual format validation (GB/T 7714 / APA 7th), suitable for daily teaching research accumulation, project conclusion output, and professional title evaluation sprints.
Paper Imitation & Pub. Expert
📚 Paper Imitation & Pub. Expert Develop an inspiring paper into your own high-quality original work step by step. Ideal for graduate students seeking to draw inspiration from excellent papers in other disciplines for topic migration, structural reconstruction, and submission optimization. 🔍 Inspiring Literature Identification: Analyze the reusable title mechanisms, problem awareness, chapter structure, theoretical framework, research methods, evidence organization, and language style of the model paper. 🔄 Interdisciplinary Paradigm Transfer: Build a 'source domain—target domain' transfer matrix to determine which ideas can be transferred and which theories, concepts, cases, and conclusions must be reconstructed. 🧠 Original Contribution Modeling: Identify literature gaps, distill core propositions and mechanisms, and check whether the paper merely changes the research object or applies a generic framework. 🧭 Research Design Planning: Supports theoretical research, case studies, qualitative research, quantitative research, literature reviews, policy text analysis, and mixed methods research. 🛡️ Real Evidence Gate: Do not fabricate data, samples, interviews, cases, statistical results, literature, or DOIs; without real evidence, do not generate false empirical conclusions. ✍️ Evidence-Driven Writing: Build argument chains via 'proposition—evidence—citation—rebuttal', generate original content chapter by chapter, and clearly mark research materials that need to be supplemented. 📈 Continuous Paper Evolution: Record each round of revisions, material gaps, and maturity changes according to L1 (topic conception), L2 (research plan), L3 (evidence formation), L4 (submission draft), and L5 (ready for submission). 🧑⚖️ Triple Simulation Review: Identify rejection risks from the perspectives of a theoretical reviewer, a method reviewer, and a target journal reviewer, and form specific revision strategies. 📨 Complete Submission Loop: Assist in generating the final paper, citation verification table, cover letter, innovation point statement, author response, revision index, and related declaration templates. ✨ Learn the paradigm, write original content, and enhance real submission competitiveness.
Social Sci Paper Coach V7.0
Loop, Audit, Anti-Hallucination, Style Align
Description
A social science academic paper writing system integrating the AFP methodology. Core features: model essay-driven imitation loop, quad-core audit mechanism, 1500-word soft truncation, hierarchical memory loading. Supports both quantitative and qualitative social science papers, including specialized mechanisms for literature authenticity verification, data anti-hallucination, and coding analysis anti-hallucination. Ready to use out of the box. Suitable for CSSCI/SSCI journal submissions, quantitative research, qualitative research, and other high-quality social science academic paper writing and journal submissions.
Related Skills
View allResearchAcademic Paper Writing v4.1
A full-process academic paper writing system that combines the Five Sources model with the AFP 3.1 three-layer architecture. Other AI tools help you "write" a paper; this one helps you "plug" every hole that could get it rejected—from one vague idea to a complete submission package in a single run through seven modules, with an anti-hallucination gate, archive-code resume, and four-core review. [10-second value] One sentence of an idea → a submittable, complete paper package. Real sources are enforced throughout, every citation is verifiable, and you can resume across sessions right where you left off. [Trigger phrases] write a paper / literature review / research method design / how to write the discussion / paper polishing / abstract & keywords / submission package [Seven modules, all fully executable instructions] Phase 1 Topic & Introduction → Phase 2 Literature Review → Phase 3 Research Method Design → Phase 4 Discussion → Phase 5 Conclusion → Phase 6 Abstract & Keywords → Phase 7 Full-Text Integration & Submission Package. Phase 0 entry routes A–G map one-to-one to the seven modules, with an R option to restore your last progress via an archive code or archived document. [v4.1 upgrades] 1. Evidence-chain gate (hard constraint): a material registry (M1/M2 numbering) + four citation elements (author / year / title / verifiable locator) + three-color marking (✅ user-supplied / ⚠️ to verify / 🚫 prohibited). If the material library is empty, the system outputs only an outline and search queries and refuses to generate body text with citations; generating references from memory or fabricating volume, issue, or page numbers is forbidden. 2. Archive-code protocol: each module ends with a structured archive code that can be saved as a YouMind document. In your next session, simply reference it with @ to resume without re-requesting already locked information. 3. Reproducible scoring: the C core anchors all dimensions to behavioral standards scored at 4/6/8/10 with stated rationale; the ratchet mechanism only moves scores upward, never downward. 4. Four-discipline configuration library (1A Humanities & Arts / 1B Social Sciences / 2A Science & Engineering / 2B Agriculture, Medicine & Life Sciences), with automatic switching of theory libraries, method toolboxes, and disciplinary norms; Category 2B runs ethics review checkpoints at Phases 0, 3, and 7. 5. Three-paradigm routing (quantitative / qualitative / theoretical): literature review narrative strategies and research method design follow different paths. 6. Anti-cliché checklist and prohibitions: discussion sections using phrases like "limited time and energy" or "pending further research," conclusions introducing new data or literature, and abstracts containing claims unsupported by the body text are all sent back by the B core. 7. Adaptivity: user profile (beginner / intermediate / proficient) + paper type (journal / thesis / conference / course) + pacing mode (default / fast-forward / slow-motion) + multi-task isolation. 8. Submission package & compliance: seven consistency checks, a six-link logic chain, reference formatting (GB/T 7714 / APA 7 / Vancouver / IEEE), ethics approval number, data availability statement, generative AI use disclosure draft, and cover letter draft. [How to use] Tell the system: your discipline, target journal / paper type / word count, and which stage you're at. The system advances module by module, pausing after each one to deliver the section, review report, scorecard, and archive code, then waits for your confirmation before continuing. [Responsibility boundaries] The system handles sources 1–4 (structure, material organization, style, integration); source 5, human calibration, is yours: academic judgment, fact-checking, and innovation decisions. All ⚠️-marked citations and data must be verified by you item by item before submission; this skill does not promise any acceptance or pass outcome.
Teaching Paper Architect
From teaching research accumulation to CSSCI/SSCI/SCI — making every teaching paper stand up to peer review. This is not a tool that writes your paper for you, but a paper architect that understands educational academic norms. It knows that IMRaD is not just four letters but a rigorous argument logic; that a literature review is not a list of references but a precise positioning of research gaps; that effect sizes are more convincing to reviewers than p-values. Seven-stage full-process coverage: Topic Focus (Innovation Three-Question Check) → Literature Review (Three-Level Coding + Funnel Writing) → Research Design (Quantitative/Qualitative/Mixed Approach Decision) → Data Analysis (Statistical Method Decision Tree) → Discussion Construction (Contribution Self-Check Matrix) → Language Refinement (AI Removal + Language Elevation + Revision Notes) → Journal Adaptation (Matching Matrix + Rejection Risk Pre-Reinforcement). Built-in Triple-Core Adversarial Engine: The Academic Writer handles output, the Language Elevation Officer polishes, and the Academic Gatekeeper has veto power—are the references real? Is the data reliable? Is the argument grounded in evidence? Does the contribution match the target journal level? Five dimensions are audited item by item; if any fail, it is sent back for rework. It doesn't just help you write well, it teaches you why the changes are made—each output includes revision notes, allowing you to truly improve your academic writing skills through iterations. Supports bilingual format validation (GB/T 7714 / APA 7th), suitable for daily teaching research accumulation, project conclusion output, and professional title evaluation sprints.
Paper Imitation & Pub. Expert
📚 Paper Imitation & Pub. Expert Develop an inspiring paper into your own high-quality original work step by step. Ideal for graduate students seeking to draw inspiration from excellent papers in other disciplines for topic migration, structural reconstruction, and submission optimization. 🔍 Inspiring Literature Identification: Analyze the reusable title mechanisms, problem awareness, chapter structure, theoretical framework, research methods, evidence organization, and language style of the model paper. 🔄 Interdisciplinary Paradigm Transfer: Build a 'source domain—target domain' transfer matrix to determine which ideas can be transferred and which theories, concepts, cases, and conclusions must be reconstructed. 🧠 Original Contribution Modeling: Identify literature gaps, distill core propositions and mechanisms, and check whether the paper merely changes the research object or applies a generic framework. 🧭 Research Design Planning: Supports theoretical research, case studies, qualitative research, quantitative research, literature reviews, policy text analysis, and mixed methods research. 🛡️ Real Evidence Gate: Do not fabricate data, samples, interviews, cases, statistical results, literature, or DOIs; without real evidence, do not generate false empirical conclusions. ✍️ Evidence-Driven Writing: Build argument chains via 'proposition—evidence—citation—rebuttal', generate original content chapter by chapter, and clearly mark research materials that need to be supplemented. 📈 Continuous Paper Evolution: Record each round of revisions, material gaps, and maturity changes according to L1 (topic conception), L2 (research plan), L3 (evidence formation), L4 (submission draft), and L5 (ready for submission). 🧑⚖️ Triple Simulation Review: Identify rejection risks from the perspectives of a theoretical reviewer, a method reviewer, and a target journal reviewer, and form specific revision strategies. 📨 Complete Submission Loop: Assist in generating the final paper, citation verification table, cover letter, innovation point statement, author response, revision index, and related declaration templates. ✨ Learn the paradigm, write original content, and enhance real submission competitiveness.
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