Policy presence
No source-backed public AI policy or guidance record is present in this profile.
The current public tracker record does not contain a source-backed claim that establishes a policy or guidance source.
Changsha, China (Mainland)
Hunan University
Hunan University is listed as QS 2026 rank =504. Hunan University has 2 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Short answer
v1 public contract
Hunan University is listed as QS 2026 rank =504. Hunan University has 2 source-backed AI policy claim records from 2 official source attributions. The public record preserves original-language evidence snippets, source URLs, snapshot hashes, confidence, and review state.
Citation-ready summary
As of this public record, University AI Policy Tracker lists Hunan University as an agent-reviewed AI policy record last checked on May 17, 2026 and last changed on May 17, 2026. The record contains 2 source-backed claims, including 2 reviewed claims, from 2 official source attributions. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/hunan-university.json. The entity-level confidence is 86%. This tracker is not legal advice, not academic integrity advice, and not an official university statement unless the linked source is the university's own official page.
Policy signals in this record
- Evidence includes Research claims.
- No specific AI service name is highlighted by the current public claim text.
- Disclosure, acknowledgment, citation, or attribution language appears in the public claim text.
Review: Agent reviewed
This reference record summarizes visible public data only. Official sources and original-language evidence remain canonical; confidence is separate from review state.
This page is not legal advice, not academic integrity advice, and not an official university statement unless a linked source is the university's own official page.
Policy profile
Deterministic source-backed dimensions derived from this record's public claims.
Review: Machine candidate
Policy profile rows are machine-candidate derived metadata. They are not final policy conclusions; inspect the linked claim evidence before reuse.
Analysis page-quality metadata is available at /api/public/v1/analysis/page-quality.json.
AI disclosure
Hunan University has 2 source-backed public claims for ai disclosure; deterministic analysis status: recommended.
Coursework
No source-backed public claim about coursework AI use is present in this profile.
The current public tracker record does not contain claim evidence about coursework, assignments, or syllabus-level AI use.
Exams
No source-backed public claim about exam AI use is present in this profile.
The current public tracker record does not contain claim evidence about exams, tests, quizzes, or examination conditions.
Privacy and data entry
No source-backed public claim about privacy or data-entry restrictions is present in this profile.
The current public tracker record does not contain claim evidence about personal, confidential, sensitive, regulated, or student data entry into AI tools.
Academic integrity
No source-backed public claim about academic-integrity treatment of AI use is present in this profile.
The current public tracker record does not contain claim evidence about AI use under academic integrity, misconduct, dishonesty, plagiarism, or cheating rules.
Approved tools
No source-backed public claim identifying approved or licensed AI tools is present in this profile.
The current public tracker record does not contain claim evidence that identifies institutionally approved, licensed, procured, or enterprise AI tools.
Named AI services
No source-backed public claim naming a specific AI service is present in this profile.
The current public tracker record does not contain claim evidence naming a specific AI service.
Teaching guidance
No source-backed public claim about teaching guidance is present in this profile.
The current public tracker record does not contain claim evidence about instructor, classroom, assessment-design, or syllabus guidance.
Research guidance
Hunan University has 2 source-backed public claims for research guidance; deterministic analysis status: recommended.
Security and procurement
No source-backed public claim about AI security review or procurement is present in this profile.
The current public tracker record does not contain claim evidence about security review, procurement, vendor approval, risk assessment, authentication, SSO, or enterprise licensing.
Coverage score measures breadth of public, source-backed coverage only. It is not a policy quality, strictness, legal adequacy, safety, or compliance score.
Evidence-backed claims
2 reviewed evidence-backed public claim
Research
The Yue Lu Public Governance editorial office states that its journal does not accept manuscripts with generative AI tools as authors, limits generative AI use in submissions to auxiliary research tasks, rejects manuscripts with AI-generated core content or concealed tool use, and requires authors who used generative AI assistance to submit an AIGC tool-use disclosure statement.
Review: Agent reviewed
Normalized value: journal_submission_aigc_disclosure_and_limits
Original evidence
Evidence 1本刊不接收任何生成式人工智能工具参与署名的稿件，稿件的原创思想、核心观点、研究设计及主体论证必须由研究者本人独立完成。生成式人工智能工具在投稿中的应用，仅限于语言润色、文献检索、数据整理与分析等辅助研究环节，不得涉及稿件核心内容的生成与创作。
Localized display only
The journal says it does not accept manuscripts with generative AI tools as authors, requires core ideas and arguments to be independently completed by researchers, and limits generative AI use to auxiliary research steps.
Research
For Hunan University's 2026 National Natural Science Foundation application notice, applicants who use generative AI to track research, collect literature, or organize references are instructed to verify AI-generated information and references, take responsibility for generated content, truthfully declare use, label relevant content under cited national rules, and not use directly AI-generated or unverified generated application content.
Review: Agent reviewed
Normalized value: research_application_ai_use_disclosure_and_verification
Original evidence
Evidence 1申请人在撰写申请书时，如果借助生成式人工智能技术跟踪研究动态、收集整理参考文献，必须由人工核实生成式人工智能生成信息和参考文献的真实性和准确性。申请人应当对使用的生成内容负责，应当全面如实声明使用情况，按照《人工智能生成合成内容标识办法》《负责任研究行为规范指引（2023）》等国家有关规定对相关内容进行标识。
Localized display only
For 2026 NSFC applications, the notice says applicants using generative AI for research tracking, literature collection, or reference organization must verify AI-generated information and references, take responsibility for generated content, truthfully declare use, and label relevant content.
Candidate claims
0 machine or needs-review claim
Candidate claims are not final policy conclusions. They preserve source URL, source snapshot hash, evidence, confidence, and review state so the record can be audited before review.
Official sources
2 source attribution
《岳麓公共治理》编辑部关于规范生成式人工智能工具使用的声明
pa.hnu.edu.cn
国自科——关于做好2026年度国家自然科学基金申请有关工作的通知
kyy.hnu.edu.cn
Change log
Source-check timeline and diff-style claim/evidence preview.
View the public change record for this university, including source snapshot hashes, claim review states, and a diff-style preview of current source-backed evidence.
Corrections and missing evidence
Corrections create review tasks and do not directly change this public record.
If an official source is missing, stale, moved, blocked, or incorrectly summarized, submit a source URL, policy change report, or institution correction for review. Corrections must preserve source URLs, source language, original evidence, review state, and audit history.