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1 = Core Problems FactHarbor Solves =
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3 (% class="box infomessage" %)
4 (((
5 **Our Mission**
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7 FactHarbor brings clarity and transparency to a world full of unclear, contested, and misleading information by shedding light on the context, assumptions, and evidence behind claims.
8 )))
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10
11 == 1. Core Problems ==
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13 === 1.1 Problem 1 — Misinformation & Manipulation ===
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15 Falsehoods and distortions spread rapidly through:
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17 * Political propaganda
18 * Social media amplification
19 * Coordinated influence networks
20 * AI-generated fake content
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22 Users need a structured system that resists manipulation and makes reasoning transparent.
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24 === 1.2 Problem 2 — Missing Context Behind Claims ===
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26 Most claims change meaning drastically depending on:
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28 * Definitions
29 * Assumptions
30 * Boundaries
31 * Interpretation
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33 FactHarbor reveals and compares these variations.
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35 === 1.3 Problem 3 — "Binary Fact Checks" Fail ===
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37 Most fact-checking simplifies complex claims into:
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39 * True
40 * Mostly True
41 * False
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43 This hides legitimate contextual differences.
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45 FactHarbor replaces binary judgment with scenario-based, likelihood-driven evaluation.
46
47 === 1.4 Problem 4 — Good Evidence Is Hard to Find ===
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49 High-quality evidence exists — but users often cannot:
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51 * Locate it
52 * Assess its reliability
53 * Understand how it fits into a scenario
54 * Compare it with competing evidence
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56 FactHarbor aggregates, assesses, and organizes evidence with full transparency.
57
58 === 1.5 Problem 5 — Claims Evolve Over Time ===
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60 Research and understanding change:
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62 * New studies emerge
63 * Old studies are retracted
64 * Consensus shifts
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66 FactHarbor provides:
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68 * Full entity versioning
69 * Verdict timelines
70 * Automatic re-evaluation when inputs change
71
72 === 1.6 Problem 6 — Users Cannot See Why People Disagree ===
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74 People often assume others are ignorant or dishonest, when disagreements typically arise from:
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76 * Different definitions
77 * Different implicit assumptions
78 * Different evidence
79 * Different contexts
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81 FactHarbor exposes these underlying structures so disagreements become understandable, not divisive.
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83
84 == 2. Core Concepts ==
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86 === 2.1 Claim ===
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88 A user- or AI-submitted statement whose meaning is often ambiguous and requires structured interpretation.
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90 A claim does not receive a single verdict — it branches into scenarios that clarify its meaning.
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92 === 2.2 Scenario ===
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94 A structured interpretation that clarifies what the claim means under a specific set of:
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96 * Boundaries
97 * Definitions
98 * Assumptions
99 * Contextual conditions
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101 Multiple scenarios allow claims to be understood fairly and without political or ideological bias.
102
103 === 2.3 Evidence ===
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105 Information that supports or contradicts a scenario.
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107 Evidence includes empirical studies, experimental data, expert consensus, historical records, contextual background, and absence-of-evidence signals.
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109 Evidence evolves through versioning and includes reliability assessment.
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111 === 2.4 Verdict ===
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113 A likelihood estimate for a claim within a specific scenario based on evidence quality, quantity, methodology, uncertainty factors, and comparison with competing scenarios.
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115 Each verdict is versioned and includes a historical timeline.
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117 === 2.5 AI Knowledge Extraction Layer (AKEL) ===
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119 The AI subsystem that interprets claims, proposes scenario drafts, retrieves evidence, classifies sources, drafts verdicts, detects contradictions, and triggers re-evaluation when inputs change.
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121 AKEL outputs follow risk-based publication model with quality gates and audit oversight.
122
123 === 2.6 Decentralized Federation Model ===
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125 FactHarbor supports a decentralized, multi-node architecture where each node stores its own data and synchronizes via federation protocol.
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127 This increases resilience, autonomy, and scalability.
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129
130 == 3. Vision for Impact ==
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132 FactHarbor aims to:
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134 * **Reduce polarization** by revealing legitimate grounds for disagreement
135 * **Combat misinformation** by providing structured, transparent evaluation
136 * **Empower users** to make informed judgments based on evidence
137 * **Support deliberative democracy** by clarifying complex policy questions
138 * **Enable federated knowledge** so no single entity controls the truth
139 * **Resist manipulation** through transparent reasoning and quality oversight
140 * **Evolve with research** by maintaining versioned, updatable knowledge
141
142 == 4. Related Pages ==
143
144 * [[Requirements (Roles)>>Archive.FactHarbor V0\.9\.23 Lost Data.Specification.Requirements.WebHome]]
145 * [[AKEL (AI Knowledge Extraction Layer)>>Archive.FactHarbor V0\.9\.23 Lost Data.Specification.AI Knowledge Extraction Layer (AKEL).WebHome]]
146 * [[Functional Requirements>>Archive.FactHarbor V0\.9\.23 Lost Data.Specification.Requirements.WebHome]]
147 * [[Federation & Decentralization>>Archive.FactHarbor V0\.9\.23 Lost Data.Specification.Federation & Decentralization.WebHome]]