Trust is built through evidence, review and responsible verification.

What Certifiedge verifies

• pathway progress
• Reality Lab submissions
• Employer Mission submissions
• portfolio artifacts
• assessment status and assessor comments
• Proof Passport entries
• certificate IDs and Royalty status
• cohort completion status
• shared evidence visibility settings

Verification confirms that a record exists in Certifiedge and has the stated status. It does not automatically guarantee job performance, employment or permanent mastery.

What Certifiedge does not guarantee

• employment
• income
• promotion
• employer acceptance
• permanent skill mastery
• error-free assessment
• Skill DNA replacing human judgment
• automatic acceptance of AI-assisted work
• public visibility of every artifact
• sample records as real credentials

Skill DNA is an evidence-informed signal. It does not replace employer review, role scoping or legal hiring obligations.

Evidence review workflow

1. Evidence is submitted with context and source notes.
2. Automated checks flag missing fields, disclosures and required artifacts.
3. Assessor reviews practical quality against rubric criteria.
4. Revision notes are issued where evidence is weak or incomplete.
5. Learner resubmits or clarifies evidence where required.
6. Final decision and readiness status are recorded in Proof Passport.
7. Verification status is updated with privacy controls preserved.

Verification and record status

Verification confirms record status inside Certifiedge. It does not guarantee employment, income, permanent competence or suitability for every role.

Proof Passport privacy and sharing

• Learners can keep records private, share selected records or publish approved views where available.
• Employers should only see evidence that is shared, authorized or otherwise permitted by program rules.
• Partner cohort reports should use aggregated or anonymized evidence where personal exposure is not required.
• Verification lookup does not expose private artifacts automatically.

AI use and originality

• AI-assisted submissions may be allowed when disclosure is complete and reviewable.
• Undisclosed AI use, fabricated citations and copied output can trigger revision, rejection or account review.
• Sensitive data should be removed before AI prompts are used unless explicit policy allows secure handling.
• Human judgment remains required for high-stakes decisions.

Content moderation principles

• remove harmful, illegal or clearly abusive submissions
• flag unverifiable claims and demand revision evidence
• protect personal and confidential data from unnecessary exposure
• record moderation decisions for audit and appeals where policy allows

Safeguarding note

Programs involving minors or vulnerable participants should apply stronger safeguarding controls, consent checks and reporting rules before scale-up.

Revision, appeal and disputes

1. Assessor marks gaps with a clear revision note.
2. Learner can revise evidence and resubmit within policy windows.
3. Learner can request clarification and, where policy allows, a second review.
4. Dispute outcomes are recorded with status history for audit trail integrity.

Research and insights data handling

Research participation should be consent-based and transparent. Reports should distinguish completed research from in-progress analysis, planned frameworks and sample structures.

Sample or illustrative datasets should always be labelled to avoid false claims.