Policy presence
University of Tabriz has 1 source-backed public claim for policy presence; deterministic analysis status: unclear.
Tabriz, Iran
University of Tabriz
University of Tabriz has 1 source-backed AI policy claim from 1 official source attribution. Review state: agent reviewed; 1 reviewed claim. Last checked May 17, 2026.
University of Tabriz AI policy short answer
v1 public contract
University of Tabriz has 1 source-backed AI policy claim from 1 official source attribution, including 1 reviewed claim. The record review state is agent reviewed; original-language evidence snippets, source URLs, confidence, and public JSON are preserved for citation. Last checked May 17, 2026. Discovery context: University of Tabriz is listed as QS 2026 rank =578.
Citation-ready summary
As of this public record, University AI Policy Tracker lists University of Tabriz as an agent-reviewed AI policy record last checked on May 17, 2026 and last changed on May 17, 2026. The record contains 1 source-backed claim, including 1 reviewed claim, from 1 official source attribution. Original-language evidence snippets and source URLs remain canonical, with public JSON available at https://eduaipolicy.org/api/public/v1/universities/university-of-tabriz.json. The entity-level confidence is 74%. 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 Source status claims.
- No specific AI service name is highlighted by the current 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
No source-backed public claim about AI disclosure or acknowledgement is present in this profile.
The current public tracker record does not contain claim evidence about disclosing, acknowledging, citing, or declaring AI use.
Coursework
University of Tabriz has 1 source-backed public claim for coursework; deterministic analysis status: conditionally_allowed.
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
University of Tabriz has 1 source-backed public claim for approved tools; deterministic analysis status: allowed.
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
University of Tabriz has 1 source-backed public claim for teaching guidance; deterministic analysis status: recommended.
Research guidance
University of Tabriz has 1 source-backed public claim 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
1 reviewed evidence-backed public claim
Source Status
The official-source crawl for University of Tabriz found an official University of Tabriz journal article about AI-based learning and faculty technostress, but this source is a research article and does not establish an institution-wide AI policy.
Review: Agent reviewed
Normalized value: official_ai_research_article_not_institutional_policy
Original evidence
Evidence 1نوع مقاله : مقاله پژوهشی. هدف: پیشرفتهای سریع فناوریهای مبتنی بر هوش مصنوعی در آموزش عالی، ضمن ایجاد فرصتهای نوین، چالشهایی همچون تکنواسترس برای اساتید دانشگاه به همراه داشته است.
Localized display only
The page labels the item as a research article and says rapid AI-based technologies in higher education create opportunities and technostress challenges for university faculty.
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
1 source attribution
تکنواسترس: چالشی نوظهور در عصر یادگیری هوش مصنوعی در میان اعضای هیات علمی دانشگاه
jkrs.tabrizu.ac.ir
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.