Āut Labs
  • Āut Labs
  • The Āutonomy Matrix
  • $AUT Token
  • Framework Intro & Components
    • Āutonomy Matrix
    • The Participation Score
      • More about Expected Contributions
    • ĀutID: a Member< >Hub bond
    • Interactions, Tasks & Contributions - a context-agnostic standard.
    • Contribution Points
      • Calculating eCP and other dependent & independent params
    • The Hub - or, the whole is greater than the sum of its parts.
    • Roles on-chain. If there is Hope, it lies in the Roles
    • Commitment Level as an RWA
      • Discrete CL Allocation
    • Peer Value
      • Flow & aggregation of value
  • 🕹️Participation Score
    • Design Thinking
      • Problems with traditional Local Reputation parameters
      • Innovation Compared to other “Local Reputation” protocols
      • Hub<>Participant Accountability & Rewards
    • Core Parameters
    • Formulæ
    • Edge Cases
      • 1. The Private Island
      • 2. Cannibal Members
      • 3. The Ghost & the House on Fire
    • PS Formula for all Edge Cases
    • Conclusions
  • 🎇Prestige
    • Prestige: introducing measurable credibility for a DAO
    • Need for a DAO to measure its KPIs overtime (on-chain)
    • Archetypes
      • Defining an Organizational Type
      • Existing Organizational Types
      • Deep-dive: Calculating current Parameters (p)
    • Formulas for Prestige
      • Normalization of p
    • Prestige for all edge cases
      • Relationship between Prestige & Archetype parameters
    • How to expand Prestige through external Data Sources
    • Use-cases & Conclusions
  • 🌎Peer Value
    • Initial Applications
    • Relationship between Participant, Hubs & Peer Value
    • Peer Value (v) as a directed graph
      • Calculating normalized Participation Score (PS'')
      • Calculating normalized Prestige (P'')
      • Calculating the Contributor Archetype (a)
    • The Peer archetype
      • Formulæ for α & deep-dives
      • Formulæ for β & deep-dives
      • Formulæ for γ & deep-dives
    • Conclusions & Initial Applications
  • ⚽Appendices & Playgrounds
    • PS Simulations
    • PS Playground
    • Prestige Simulations
    • Prestige Playground
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  1. Peer Value

The Peer archetype

Initial Parameters for υ\upsilonυ

Initially, we will be using three (3) main parameters for evaluating an individual’s Peer Value (Global Reputation):

  • The Centrality ( α\alphaα ) of the contribution of a Participant across their Hubs.

  • The Betweenness (Interconnection) ( β\betaβ ) of a Participant respect to their peers.

  • The Variety ( γ\gammaγ ) in the Contributions delivered by a Participant across all their Hubs.

On a concrete level, they also identify the main "archetypes" of a value-contributor:

  • The Pillar ( α\alphaα )

  • The Socialite ( β\betaβ )

  • The Polymath ( γ\gammaγ )

From these archetype we can extract a compound parameter, called Peer archetype ( a˚\mathring{a} a˚ ):

a˚(j,H⋅)=(wα×α)+(wβ×βj)+(wγ×γ)3 \displaystyle \mathring{a}_{\tiny (j, \tt H \cdot)} = \frac {(w_{\tiny \alpha} \times \alpha) + (w_{\tiny \beta} \times β_{\tiny j}) + (w_{\gamma} \times \gamma)} {3}a˚(j,H⋅)​=3(wα​×α)+(wβ​×βj​)+(wγ​×γ)​

where:

  • a˚j,N⋅\mathring{a}_{j, \tt N \cdot}a˚j,N⋅​ is the Peer archetype of Participant j across all their Hubs [h⋅][\tt h \cdot][h⋅] in the set [H⋅][\tt H \cdot][H⋅].

  • α\alphaα is the Centrality of j's Participation Score (PS) in all their Hubs.

  • β\betaβ is the Interconnection (Betweenness) of j with their peers.

  • γ\gammaγ is the variety of j’s contributions across their Hubs

The dominant parameter will determine the Archetype of the Contributor j.

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Last updated 2 months ago

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