Document Type: Model
Status: Active Model
Version: v1.1
Authority: Research Brain
Parent: Research Brain Architecture
Applies To: All external and internal sources referenced during research
Linked Systems:
Research Brain Offer Source Validation Framework
Research Intelligence Database
MWMS Data Governance Standards
Last Reviewed: 2026-04-19
Purpose
Defines how Research Brain records sources used during research so information remains:
traceable
auditable
reusable
comparable
The registry supports:
evidence transparency
research reproducibility
signal reuse
long-term intelligence accumulation
editorial authority interpretation
source ecosystem pattern recognition
The model enables Research Brain to identify patterns in where reliable intelligence originates and how source environments influence decision quality.
Scope
This model applies to:
external research references
internal structured intelligence inputs
market research sources
competitor references
editorial publications
industry analysis sources
technical documentation
behavioural research inputs
SEO authority sources
media ecosystem sources
This model governs source classification logic.
It does not govern:
research methodology selection
experiment design decisions
hypothesis validation logic
data schema design
platform analytics interpretation
Those remain governed by other Research Brain frameworks.
Core Principle
Sources are intelligence signals.
The value of a source is determined by:
relevance
credibility
context
repeatability
ecosystem relationship
signal consistency
Source value must not be reduced to popularity alone.
Strong research requires diverse and contextually appropriate source environments.
Source Registry Fields
Each source entry may record:
Source Type
Source Category
Source Context
URL or identifier
Observation relevance
Confidence impact level
Topical relevance level
Source environment classification
Signal persistence relevance
Source Type Classification
Examples of source types include:
Primary page
competitor page
educational content
market signal
structural reference
journal publication
editorial publication
trade publication
technical documentation
dataset source
behavioural research reference
expert commentary source
Source type helps determine interpretation weighting.
Source Category Classification
Source category provides contextual classification of the environment producing the information.
Examples:
competitor environment
academic environment
media environment
technical environment
practitioner environment
regulatory environment
community environment
platform environment
Category classification supports pattern clustering.
Source Context
Source context describes how the source is used within the research task.
Examples:
market validation
structural validation
behavioural interpretation
competitive comparison
tactical learning
environmental scanning
authority validation
signal confirmation
Context prevents misinterpretation of source purpose.
Editorial Source Environment Layer
Editorial environments represent a distinct source category due to their influence on authority formation and signal distribution.
Editorial source environments may include:
national publications
trade publications
regional publications
niche publications
expert commentary environments
journalist request environments
industry news environments
Editorial sources contribute to:
authority signals
narrative propagation
topic legitimisation
credibility signalling
Editorial relevance must be interpreted alongside subject relevance.
Topical Relevance Field
Topical relevance reflects how closely the source aligns with the subject domain.
Relevance influences interpretability of signals.
High topical relevance may increase:
confidence interpretability
signal contextual clarity
insight transferability
Low topical relevance may still provide value but should be weighted accordingly.
Relevance must be assessed relative to the research objective.
Confidence Impact Level
Confidence impact level reflects how strongly the source influences research confidence.
Confidence must consider:
evidence quality
context alignment
methodological rigour
source credibility
corroboration potential
Confidence must not be increased purely by repetition of the same source.
Repeated appearance of a source does not automatically increase reliability.
Source Environment Diversity Principle
Reliable research requires diversity of source environments.
Over-reliance on a single environment increases bias risk.
Diversity may include variation across:
publication type
expertise domain
geographic perspective
methodological perspective
industry perspective
Source diversity strengthens interpretability robustness.
Signal Persistence Field
Some sources indicate stable structural patterns.
Examples:
recurring frameworks
repeated behavioural observations
repeated structural models
persistent market signals
Signal persistence relevance may indicate:
structural durability
transferable intelligence
reusable models
Persistent signals should be tracked longitudinally.
Reuse Rule
Sources may be reused across multiple research tasks.
Reuse must not inflate confidence.
Repeated citation must not substitute independent validation.
Sources should be evaluated according to:
context relevance
evidence strength
methodological alignment
Reuse supports pattern recognition.
Reuse does not replace verification.
Editorial Authority Awareness Rule
Editorial sources may influence market perception beyond direct informational content.
Editorial environments can affect:
credibility perception
topic visibility
narrative propagation
market attention
Editorial authority must be recognised as a signal environment rather than treated solely as informational content.
Editorial sources should be interpreted alongside other source categories.
Source Registry Role
The registry is not a bibliography.
The registry is an intelligence tracking structure.
Sources help future research:
understand signal patterns
identify recurring structures
detect emerging opportunity clusters
track authority environment signals
identify repeated ecosystem structures
The registry enables longitudinal intelligence accumulation.
Relationship to Other MWMS Systems
Supports:
Research Intelligence Database
Research Brain Offer Source Validation Framework
Research Signal Logging Structure
Research Verdict Framework
Channel Classification systems
authority signal interpretation systems
Source registry improves cross-framework signal continuity.
Drift Protection
The system must prevent:
source popularity bias replacing relevance evaluation
single-source over-reliance
repeated citation misinterpreted as independent confirmation
authority signals treated as proof of correctness
weak contextual sources inflating confidence
Sources must remain interpretable within research context.
Architectural Intent
The Research Source Registry Model enables Research Brain to accumulate structured intelligence over time.
Tracking sources consistently improves:
pattern recognition
structural interpretation
research transparency
signal reuse efficiency
authority environment awareness
The registry supports the development of durable intelligence assets rather than isolated research outputs.
Change Log
Version: v1.0
Date: 2026-03-26
Author: HeadOffice
Change:
Initial creation of Research Source Registry Model defining structured tracking model for research sources used across research tasks.
Version: v1.1
Date: 2026-04-19
Author: HeadOffice
Change:
Expanded model to include editorial source environment awareness, topical relevance classification, source diversity considerations, and signal persistence relevance to support authority-aware research interpretation and long-term intelligence continuity.
END Research Brain Research Source Registry Model v1.1