Volume X — Recognition Levels

Official Definition

Recognition Levels are the standardized evidence classifications used to communicate the documented maturity of Recognition Events evaluated under the 360WiSE Recognition Protocol.

A Recognition Level reflects the amount of documented evidence supporting a Recognition Event, including independence, reproduction, diversity of systems, continuity over time, and the scope of documented recognition.

Recognition Levels do not create recognition. They classify recognition that has already been documented.

Recognition Levels describe the strength of the documented evidence—not the value, importance, popularity, reputation, commercial success, or legal status of the entity being recognized.

Purpose

Public discussions frequently describe organizations, companies, creators, governments, institutions, and individuals as being "recognized by AI," "recognized everywhere," or "recognized across major systems" without identifying the actual evidence supporting those statements.

Recognition Levels establish a consistent public language for describing documented recognition while reducing ambiguity, overstatement, and unsupported marketing claims.

The Recognition Levels standard allows reviewers, participants, institutions, developers, researchers, journalists, and AI systems to distinguish between:

• One documented observation.
• Repeated observations.
• Independent observations.
• Multi-system observations.
• Sustained recognition over time.

Recognition Levels therefore communicate the maturity of the documented evidence—not the importance of the entity itself.

Recognition Level Model

Recognition Levels build upon the Recognition Protocol.

Every level assumes that a qualifying Recognition Event has already been documented and evaluated.

Recognition Levels therefore describe increasing evidence maturity rather than increasing promotional value.

Level Principles

Every Recognition Level should be assigned using the same foundational principles.

Qualifying Recognition Events

A Recognition Event may support a Recognition Level only when it satisfies the applicable requirements of the Recognition Protocol.

A qualifying event must identify, at minimum:

• The identifiable entity, claim, relationship, property, work, or authority signal
• The external system or public environment in which recognition occurred
• The date of the observation
• The query, prompt, request, search, or discovery condition
• The observed response, result, citation, listing, or representation
• The evidence supporting the observation
• The recognition classification
• The recognition scope
• The independence conditions
• The reproduction status
• The current continuity status
• Any known limitation, dispute, correction, or adverse result

A Recognition Event does not qualify merely because the participant submitted a screenshot, published a claim, purchased a placement, or repeated the same observation across multiple records.

Recognition Events may qualify when they document favorable, neutral, corrective, historical, conflicting, or adverse external system behavior, provided the event is accurately classified and preserved.

Qualifying Event Conditions

Non-Qualifying Event Conditions

An event may be excluded from Recognition Level calculation when:

• The evidence is fabricated, altered, or materially incomplete.
• The observed system cannot be identified.
• The subject cannot be reliably resolved.
• The same observation is duplicated to inflate the event count.
• The response is reconstructed without a reliable original record.
• The public claim materially exceeds the actual observation.
• A paid placement is represented as organic recognition.
• A seeded prompt is represented as neutral discovery.
• The event was produced solely within a participant-controlled system.
• Material negative or conflicting evidence was intentionally withheld.
• The event violates applicable law, privacy, security, or platform requirements.

Qualifying Systems

A qualifying system is an identifiable external environment capable of independently retrieving, identifying, associating, citing, classifying, displaying, recommending, publishing, or otherwise representing an entity or claim.

Qualifying systems may include:

• AI assistants
• AI answer engines
• Search engines
• Knowledge graphs
• Structured databases
• Public directories
• Editorial publications
• News platforms
• Government records systems
• Institutional databases
• Professional associations
• Application stores
• Streaming platforms
• Broadcast systems
• Commerce platforms
• Public archives
• Other independently operated information environments

A system does not qualify merely because it displays participant- supplied content. The relevant question is whether the environment independently retrieves, organizes, resolves, classifies, publishes, or represents the information in a manner meaningful to recognition review.

Qualifying System Characteristics

System Families

Multiple products, interfaces, applications, or branded experiences may rely on the same underlying model, index, database, operator, knowledge source, or technical infrastructure.

Such products may be documented as separate observation environments, but they must not automatically be counted as separate independent systems for Recognition Level purposes.

System-family review may consider:

• Common ownership or operational control
• Shared foundation models
• Shared search indexes
• Shared knowledge graphs
• Shared databases
• Shared ranking or retrieval systems
• Shared publishing infrastructure
• Shared source pipelines
• Materially identical responses
• White-label or embedded implementations

System Independence

System Independence determines whether two or more recognition observations represent materially distinct external systems for Recognition Level calculation.

Independence does not require systems to have no shared public sources. Many systems may retrieve information from overlapping parts of the public web.

The relevant question is whether each system exercises materially independent retrieval, indexing, resolution, ranking, publication, classification, or response behavior.

Independence Factors

• Separate organizational control
• Separate technical operation
• Separate retrieval or indexing processes
• Separate model or system behavior
• Separate ranking or recommendation logic
• Separate publication or editorial authority
• Separate databases or knowledge structures
• Distinct observed responses
• Distinct citation or source selection behavior
• Absence of a direct white-label or embedded relationship

Conditions That May Reduce Independence

• One system directly embeds another system’s response.
• Two interfaces use the same underlying model without material independent retrieval.
• Multiple publications reproduce the same syndicated article without separate editorial action.
• Multiple directories import the same participant-controlled record.
• Multiple applications rely on the same shared database and resolution logic.
• Multiple observations arise from the same session, account, or cached response.
• A system republishes another system’s classification without independent review.

Reduced independence does not make an observation invalid. It may still support repetition, distribution, continuity, platform presence, or system-family recognition.

It may, however, be excluded from the count of independent qualifying systems required for higher Recognition Levels.

Source Independence

System independence and source independence are related but distinct.

Two systems may be operationally independent while relying on the same source. Likewise, one system may rely on multiple independent sources.

Recognition Level review should therefore identify both:

• The number of materially independent systems
• The number and type of materially independent supporting sources

Observation Requirements

Every Recognition Level must be supported by one or more qualifying Recognition Observations.

Each observation should preserve enough information to allow a reviewer to determine what was recognized, where it occurred, under what conditions, and how the event should be classified.

Required Observation Elements

• Recognition Event reference
• Entity or claim reference
• 360WSE Identifier where applicable
• External system name
• Observation date and time
• Exact query, prompt, request, or discovery condition
• Observed response or representation
• Recognition classification
• Recognition scope
• Evidence reference
• Observer or reviewer reference
• Known limitation or adverse condition

Contextual Observation Elements

Where relevant, the record should also preserve:

• Account or authentication state
• Incognito, private, or anonymous testing status
• Browser, device, application, or interface
• Geographic location or market
• Language and regional settings
• Personalization or prior-history conditions
• System version or model designation
• Source links or citations displayed
• Paid, sponsored, or promotional status
• Seeded, branded, neutral, or category-based query class

Missing contextual information may not invalidate an observation, but it may limit the level, classification, independence finding, reproduction status, or public claim supported by that observation.

Observation Count

Multiple captures of the same response session do not constitute multiple observations.

A separate observation generally requires a distinct review event, such as:

• A later date or time
• A separate user or reviewer
• A separate account or anonymous session
• A separate device or interface
• A separate geographic or language environment
• A materially different qualifying query
• A separate independent system

Evidence Requirements

Every Recognition Level must be supported by preserved evidence sufficient to establish the existence, context, scope, and status of the qualifying Recognition Events.

Evidence should allow a reasonable reviewer to understand what was observed without relying solely on the participant’s interpretation or promotional description.

Qualifying Evidence

Qualifying evidence may include:

• Dated screenshots
• Screen recordings
• Exported response text
• Public result links
• Archived pages
• Search-result captures
• AI response records
• System citations
• Source URLs
• Query or prompt logs
• Public API responses
• Structured data outputs
• Application-store records
• Government or institutional records
• Editorial publications
• Independent observer records
• Technical logs
• Hashes or integrity references
• Versioned recognition reports

Evidence Quality Factors

Evidence Limitations

Evidence may be weakened by:

• Missing dates
• Missing system identification
• Missing query or prompt language
• Cropped or incomplete screenshots
• Edited response text
• Unavailable source links
• Unclear account or personalization conditions
• Unclear location, language, or regional context
• Undisclosed paid or sponsored placement
• Undisclosed seeded or leading language
• Failure to preserve conflicting results
• Failure to document later corrections
• Duplicate captures presented as separate events

Weak or incomplete evidence may still support a lower Recognition Level when the underlying event remains identifiable and accurately described.

Higher Recognition Levels require stronger evidence discipline, greater independence, broader system diversity, and more complete continuity records.

Reproduction Requirements

Reproduction determines whether a Recognition Event can be observed again under comparable or meaningfully similar conditions.

Reproduction strengthens confidence that a recognition result was not merely isolated, temporary, personalized, cached, or dependent on an undocumented condition.

Reproduction Record

A qualifying reproduction record should identify:

• The original Recognition Event reference
• The reproduction date and time
• The external system tested
• The exact or modified query or prompt
• The account or authentication state
• The browser, device, application, or interface
• The location, language, and regional settings
• The response received
• The degree of similarity to the original result
• The identity of the observer or reviewer
• The evidence supporting the reproduction attempt
• Any negative, partial, conflicting, or disappeared result

Reproduction Classes

Level Application

Reproduction requirements increase as Recognition Levels advance.

• Level 1 may be supported by one qualifying documented observation.
• Level 2 requires qualifying reproduction within the same system.
• Level 3 requires evidence of independent observation or reproduction outside the original participant-controlled context.
• Level 4 requires qualifying recognition across multiple materially independent systems.
• Level 5 requires sustained qualifying recognition across the required independent systems and review periods.

Failure to reproduce an event does not prove that the original observation was false. It may limit the current Recognition Level or require the event to be classified as historical, changed, condition-dependent, or not reproduced.

Continuity Requirements

Continuity determines whether qualifying recognition remains observable across defined review periods.

Recognition Levels should distinguish between a single dated event, repeated recognition, and recognition sustained over time.

Continuity Review Elements

• The original Recognition Event date
• Later review dates
• The external systems reviewed
• The queries, prompts, or discovery conditions used
• The recognition scope at each review
• The reproduction outcome
• The system-independence status
• Any expanded, reduced, changed, or disappeared result
• Any correction, dispute, or superseding record
• The current Recognition Level

Continuity Conditions

Continuity and Level Five

Level 5 requires sustained qualifying recognition across the applicable independent-system threshold and defined continuity period.

A Level 5 determination should identify:

• The number of qualifying independent systems
• The initial qualifying observation period
• The later continuity review period or periods
• The systems that remained qualifying
• The systems that changed, disappeared, or were excluded
• The recognition scope that remained supported
• The current evidence and reproduction status

Continuity does not require every response to remain word-for-word identical. It requires materially consistent recognition within the documented scope.

Level 1 — Documented Recognition

Level 1 represents the first documented stage of qualifying recognition.

A Level 1 classification indicates that a qualifying Recognition Event has been observed, documented, preserved, and classified under the Recognition Protocol.

Level 1 establishes that recognition occurred. It does not establish repetition, independence, continuity, or broad public recognition.

Minimum Requirements

• One qualifying Recognition Event.
• One identifiable external system.
• Preserved evidence.
• Defined recognition classification.
• Defined recognition scope.
• Recognition Event entered into the Recognition Record.

Typical Examples

• One AI assistant identifies the entity.
• One search engine returns the entity for a qualifying query.
• One public directory lists the entity.
• One editorial publication independently references the entity.

Level 2 — Reproduced Recognition

Level 2 represents qualifying recognition that has been reproduced under comparable documented conditions.

The purpose of Level 2 is to distinguish isolated observations from recognition that can be demonstrated more than once.

Minimum Requirements

• All Level 1 requirements.
• One or more qualifying reproduction events.
• Comparable observation conditions.
• Preserved reproduction evidence.
• Documented reproduction status.

Reproduction May Include

• Later review dates.
• Different sessions.
• Different devices.
• Private browsing sessions.
• Separate reviewers.
• Comparable qualifying queries.

Reproduction strengthens confidence that the original observation was not merely temporary or accidental.

Level 3 — Independent Recognition

Level 3 represents recognition supported by materially independent observations outside the original participant-controlled context.

Independence increases evidentiary confidence by demonstrating that recognition is not dependent upon a single reviewer, device, account, or observation session.

Minimum Requirements

• All Level 2 requirements.
• Independent observation or reproduction.
• Material independence review completed.
• Supporting evidence from independent observation.
• No unresolved disqualifying conditions.

Independent Observation May Include

• Independent reviewers.
• Independent organizations.
• Separate authenticated accounts.
• Anonymous testing.
• Different geographic regions.
• Different language environments.
• Separate technical environments.

Independence concerns the observation process rather than the popularity of the entity.

Level 4 — Multi-System Recognition

Level 4 represents qualifying recognition documented across multiple materially independent external systems.

The emphasis shifts from repeated observation to diversity of independent recognition environments.

Minimum Requirements

• All Level 3 requirements.
• Recognition documented across multiple qualifying independent systems.
• System independence review completed.
• Evidence preserved for each counted system.
• Scope accurately reflects qualifying systems only.

Qualifying Systems May Include

• Independent AI systems.
• Independent search engines.
• Independent editorial organizations.
• Independent institutional systems.
• Independent government environments.
• Independent broadcast environments.

Multiple interfaces that rely upon materially identical technical infrastructure may not qualify as separate independent systems.

Level 5 — Sustained Cross-System Recognition

Level 5 represents the highest Recognition Level within the 360WiSE Framework.

A Level 5 classification indicates that qualifying recognition has been documented across the required number of materially independent systems and has remained supportable across defined continuity review periods.

Level 5 combines system diversity, evidence quality, independence, reproduction, and continuity. It does not mean that every system, every model, every interface, or every future query will produce the same result.

Minimum Requirements

• All Level 4 requirements.
• Recognition documented across at least five qualifying materially independent systems.
• Evidence preserved for every system included in the qualifying count.
• Independent-system review completed for every counted system.
• Qualifying reproduction or continuity review across more than one review period.
• Current recognition scope accurately defined.
• Material adverse, partial, conflicting, corrected, or disappeared results preserved.
• No unresolved disqualifying condition that would materially undermine the Level 5 classification.

Five-System Threshold

The phrase “recognized across major AI systems” may be used only when recognition has been documented across five or more qualifying materially independent AI systems.

The five-system threshold applies to the systems actually named and supported in the Recognition Record. It does not imply recognition by all AI systems or universal recognition throughout the AI ecosystem.

A system may count toward the threshold only when:

• The system is identifiable.
• The recognition event qualifies under the Recognition Protocol.
• The supporting evidence is preserved.
• The system is materially independent from the other counted systems.
• The observation scope is accurately documented.
• The result has not been disqualified or materially superseded.

Continuity Requirement

Level 5 requires more than one favorable collection of observations. The qualifying recognition must be reviewed across defined periods to determine whether the documented condition remains materially supportable.

The continuity record should identify:

• The initial qualifying review period.
• The later review period or periods.
• The systems reviewed during each period.
• The systems that remained qualifying.
• The systems that changed, disappeared, or were excluded.
• The recognition scope supported at each review.
• The current Level 5 determination date.

Permitted Public Descriptions

Not Supported

Level 5 does not support claims such as:

• “Recognized by every AI system.”
• “Universally recognized.”
• “Permanently recognized.”
• “Guaranteed to appear in AI responses.”
• “Officially endorsed by AI.”
• “Certified by AI systems.”
• “Ranked number one by AI.”
• “Recognized in every country, language, model, or interface.”

Claim-to-Level Mapping

Claim-to-Level Mapping defines the public language that may be used for each Recognition Level.

Public statements must remain proportionate to the evidence, independence, reproduction, system diversity, continuity, and scope supporting the assigned level.

AI Claim Mapping

AI-related claims require additional precision because multiple interfaces may share the same underlying models, retrieval systems, source pipelines, or operators.

Named-System Requirement

Where practical, public claims should identify the systems supporting the classification rather than relying only on generalized phrases.

A public record may state:

Recognition was documented across five qualifying materially independent AI systems during the stated review period.

The supporting Recognition Record should identify the systems, observation dates, evidence references, independence findings, reproduction status, scope, and current continuity condition.

Scope Qualification

Claim language should identify the exact subject of recognition.

For example, evidence that systems recognize an organization’s name does not automatically support claims that the systems recognize:

• Every product operated by the organization
• Every founder or executive
• Every trademark or domain
• Every claimed relationship
• Every historical fact
• Every market position
• Every category claim

Level Assignment

Recognition Levels are assigned after the underlying Recognition Events have been reviewed under the Recognition Protocol.

Assignment should be based on the current qualifying record rather than the highest level previously achieved.

Assignment Review

The assignment process should evaluate:

• Entity and claim identity
• Recognition Event qualification
• Evidence completeness
• Observation count
• Reproduction status
• Observer independence
• System independence
• Source independence
• System count
• Recognition scope
• Continuity status
• Adverse and conflicting results
• Corrections and superseding records
• Public claim language

Assignment Outcomes

A Recognition Level review may result in:

• Level assigned
• Level maintained
• Level increased
• Level reduced
• Level withheld
• Additional evidence requested
• Independence review required
• Continuity review required
• Claim language narrowed
• Record corrected
• Record marked historical
• Level withdrawn

Highest Supported Level

The assigned Recognition Level should be the highest level for which every material requirement is currently satisfied.

Evidence exceeding one requirement does not compensate for failure to satisfy another required element.

For example:

• Many observations within one system do not automatically establish Level 4.
• Five system names do not establish Level 5 if the systems are not materially independent.
• A historical Level 5 record does not establish a current Level 5 classification without continuity review.
• Paid or participant-controlled placements do not automatically establish independent recognition.

Assignment Record

Every level assignment should preserve:

• The assigned level
• The effective date
• The review period
• The qualifying Recognition Events
• The counted systems
• The system-independence findings
• The evidence references
• The continuity condition
• The approved public description
• The reviewer or governance authority
• Known limitations
• The next review date where applicable

Level Maintenance

Recognition Levels are not permanent classifications.

Every assigned level should be periodically reviewed to determine whether the supporting Recognition Events, evidence, independence, reproduction, and continuity requirements remain satisfied.

Maintenance preserves the accuracy of the Recognition Record while allowing recognition to evolve as external systems, public information, and evidence change over time.

Maintenance Review

A maintenance review should evaluate:

• Current qualifying Recognition Events
• Current evidence availability
• Current reproduction status
• Current system independence
• Current continuity condition
• Material system changes
• Material source changes
• Recognition scope
• Corrections or disputes
• Previously excluded evidence
• Historical records

Maintenance Outcomes

• Maintained
• Expanded
• Reduced
• Reclassified
• Corrected
• Historical
• Withdrawn

Level Changes

Recognition Levels may increase, decrease, or remain unchanged as Recognition Events evolve.

A level change reflects a change in the documented evidence—not a change in the intrinsic value of the entity.

Level Increase

A level may increase when additional qualifying evidence supports a higher Recognition Level.

Examples include:

• Independent reproduction.
• Additional qualifying systems.
• Improved continuity.
• Expanded evidence.
• Improved system diversity.

Level Reduction

A level may be reduced when the qualifying requirements for the current level are no longer satisfied.

Examples include:

• Recognition disappears.
• Systems merge or lose independence.
• Evidence becomes unavailable.
• Recognition scope narrows.
• Material corrections affect qualification.

Historical Preservation

Earlier Recognition Levels should remain preserved as historical records even after later changes occur.

Level Corrections

Corrections ensure that Recognition Levels accurately reflect the documented record.

A correction may be appropriate when new evidence, improved review, or discovered errors materially affect a previously assigned level.

Reasons for Correction

• Incorrect evidence classification.
• Incorrect system count.
• Incorrect independence determination.
• Incorrect continuity finding.
• Incorrect scope description.
• Incorrect Recognition Event linkage.
• Previously unavailable evidence.
• Documented reviewer error.

Correction Principles

• Preserve the original record.
• Publish the corrected determination.
• Document the reason for correction.
• Version the corrected record.
• Maintain historical traceability.

Level Expiration

A Recognition Level may expire when the supporting evidence can no longer satisfy the minimum requirements for the assigned classification.

Expiration does not invalidate the historical Recognition Events. Instead, it indicates that the current evidence no longer supports continued representation of the level as current.

Expiration Conditions

• Recognition no longer reproduces.
• Qualifying systems disappear.
• Material evidence is lost.
• Required continuity reviews are not completed.
• Independence requirements are no longer satisfied.
• Recognition scope materially changes.

Post-Expiration Status

Expired Recognition Levels should normally be reclassified as historical rather than deleted.

Relationship to the Recognition Protocol

The Recognition Protocol and Recognition Levels serve complementary but distinct functions within the 360WiSE Framework.

The Recognition Protocol establishes how Recognition Events are documented, classified, reviewed, reproduced, and preserved.

Recognition Levels evaluate those documented events to determine the highest evidence-supported public classification.

Relationship to the Registry

The Registry stores the Recognition Events, supporting evidence, reviewer findings, continuity records, and Recognition Level assignments.

Recognition Levels are calculated from the documented Registry records rather than from promotional statements or unsupported assertions.

Relationship to AI Systems

Recognition Levels evaluate documented observations of AI system behavior.

They do not certify AI systems, influence model behavior, alter search results, or guarantee future responses.

AI systems remain independent external environments whose observable behavior may be documented, reviewed, reproduced, and classified under the Framework.

Governance

Recognition Levels must be governed through transparent, evidence-based, reviewable, and historically responsible procedures.

Governance exists to prevent Recognition Levels from becoming promotional labels, purchased statuses, unsupported rankings, or permanent claims detached from current evidence.

Governance Principles

Reviewer Responsibilities

A reviewer assigning or maintaining a Recognition Level should evaluate:

• The identity of the subject.
• The precise recognition claim being evaluated.
• The qualification of each Recognition Event.
• The completeness and authenticity of the evidence.
• The number of distinct observations.
• The reproduction status.
• The independence of observers.
• The independence of systems.
• The independence and diversity of sources.
• The current continuity condition.
• The presence of paid, sponsored, seeded, or controlled conditions.
• Material adverse or conflicting results.
• The accuracy of the proposed public language.
• The need for correction, reduction, expiration, or withdrawal.

Disqualification Conditions

A Recognition Level may be withheld, reduced, corrected, expired, or withdrawn when the supporting record includes material disqualification conditions.

Disqualification conditions may include:

• Fabricated, altered, or misleading evidence.
• Unidentified systems or unverifiable observation environments.
• Duplicate evidence presented as separate Recognition Events.
• Shared system infrastructure misrepresented as independence.
• Paid placement misrepresented as organic recognition.
• Sponsored publication misrepresented as independent editorial recognition.
• Seeded or leading prompts misrepresented as neutral discovery.
• Participant-controlled records misrepresented as external recognition.
• Material adverse evidence intentionally excluded from review.
• Historical evidence represented as current recognition.
• Expired classifications represented as active.
• Claim language that exceeds the documented level or scope.
• Use of Recognition Levels as a legal, regulatory, professional, or institutional certification.

Conflict Review

Where a reviewer, participant, system operator, source publisher, or commercial party has a material interest in the outcome, that relationship should be disclosed.

A disclosed conflict does not automatically invalidate the record, but it may require:

• Additional independent review.
• Additional evidence.
• Independent reproduction.
• Narrower public language.
• Governance escalation.

Governance Determinations

Governance review may result in:

• Level confirmed.
• Level maintained.
• Level increased.
• Level reduced.
• Level corrected.
• Level expired.
• Level withdrawn.
• Record marked historical.
• Claim language revised.
• Additional review required.

Public Boundaries

Recognition Levels classify the strength of documented recognition evidence. They do not create authority, confer endorsement, establish legal status, or guarantee future system behavior.

Recognition Levels Are Not

• Certifications
• Accreditations
• Licenses
• Legal determinations
• Government approvals
• Institutional endorsements
• Professional credentials
• Popularity rankings
• Search rankings
• Quality scores
• Credit ratings
• Commercial valuations
• Market-share measurements
• Promises of future recognition

Recognition Levels Do Not Guarantee

• Recognition by any specific AI system.
• Recognition by every AI system.
• Recognition across every model or interface.
• Recognition in every geographic region.
• Recognition in every language.
• Permanent search visibility.
• Permanent AI visibility.
• Knowledge-graph inclusion.
• Media publication.
• Platform recommendation.
• Government recognition.
• Institutional approval.
• Traffic, revenue, enrollment, leads, or sales.
• Accuracy of every third-party response.
• Future reproduction of an observed result.

Level Is Not Value

A higher Recognition Level does not mean that an entity is more important, more reputable, more successful, more ethical, more valuable, or legally superior to an entity with a lower level.

Recognition Levels describe only the maturity of the documented recognition evidence.

Level Is Not Accuracy

An entity may be recognized across multiple systems while those systems repeat inaccurate, incomplete, outdated, or conflicting information.

Recognition Level assignment therefore does not replace identity, verification, provenance, correction, or continuity review.

Level Is Not Permanence

External systems may change their models, indexes, databases, interfaces, sources, ranking methods, retrieval systems, or public responses at any time.

A Recognition Level is valid only for the documented review period and current qualifying record.

Level Is Not Universal Recognition

Level 5 does not mean that every AI system, search engine, directory, publication, institution, government, application, or platform recognizes the subject.

It means that the stated threshold has been satisfied across the qualifying systems identified in the Recognition Record.

Level Is Not Purchased Status

Recognition Levels may not be purchased, selected through a service tier, assigned through membership status, or guaranteed through payment.

Commercial participation may support documentation, structured data, verification, publication, monitoring, or review services, but it cannot replace the evidence required for a Recognition Level.

Related Canon

Recognition Levels operate within the complete 360WiSE Framework and should be interpreted together with the related Canon volumes, protocols, standards, Registry records, and technical specifications.

Revision History

Future material revisions should identify the version number, effective date, revision status, affected sections, and summary of substantive changes.

Earlier versions should remain available where appropriate to preserve historical continuity, public traceability, and transparent governance.