Latest revision as of 13:13, 12 March 2025

Mycelith Voting System

The Mycelith Voting System is a decentralized, senary-based decision-making mechanism designed to ensure transparent, fair, and ethically governed voting within the Seigr ecosystem. Mycelith directly integrates with the Rebel Earthling License (RE-L) to enforce ethical compliance, track contributor influence, and uphold fair resource allocation.

Mycelith is designed to be:

Adaptive – Decisions evolve across six structured layers, mirroring the decentralized intelligence of mycelial networks.
Transparent – All votes are publicly auditable, and contributions are traceable via Contribution Units (CUs).
Resilient – Voting outcomes dynamically adjust based on long-term community engagement and commitment.

Mycelith & RE-L: Ethical Voting in Seigr

Unlike traditional voting systems, Mycelith ensures that decisions:

Are directly linked to Contribution Units (CUs) – A participant’s voting weight is proportional to their documented contributions.
Reinforce ethical licensing – Votes that contradict RE-L’s ethical compliance can be flagged by Hyphen Nodes for review.
Are governed by Seigr-Native enforcement – All Mycelith outcomes are executed via Seigr Capsules.

This ensures that voting power is earned through verifiable contributions rather than arbitrary social metrics.

Six-Layer Voting Structure

Mycelith is structured around six sequential voting layers, where each layer increases the influence of consistent participants. Each layer ( $L_{1}$ to $L_{6}$ ) allows for vote refinement, discussion, and weighted commitment tracking.

Layer	Description	Influence Scaling
Layer 1 (Initiation)	Initial vote, minimal weight.	$S_{1}=1.0$
Layer 2 (Observation)	Minor weight increase; early revisions allowed.	$S_{2}=1.2$
Layer 3 (Consensus Building)	Influence increases as participants justify positions.	$S_{3}=1.44$
Layer 4 (Commitment Phase)	Higher weight to consistent votes; switching is penalized.	$S_{4}=1.728$
Layer 5 (Final Validation)	Near-max influence; Hyphen Nodes review integrity.	$S_{5}=2.0736$
Layer 6 (Execution Layer)	Decision is finalized and executed via Seigr Capsules.	$S_{6}=2.48832$

Contribution-Based Voting Weight (CBVW)

Each participant’s voting influence is directly linked to their Contribution Units (CUs). This is measured by the Contribution-Based Voting Weight (CBVW), replacing the outdated WCAS system.

Let:

$V_{i}$ be participant $i$ ’s base voting weight.
$W_{i}$ be their weighted influence based on their Contribution Units.

Aggregating Votes for the Final Decision

The final vote outcome $O$ is determined using senary influence scaling.

Each participant’s weighted vote is calculated as:

$W_{j}^{(i)}=W_{i}\cdot S_{j}$

where:

$W_{i}$ is the participant's base weight.
$S_{j}$ is the senary scaling factor at layer $j$ .

Votes are aggregated using:

$O={\text{sign}}\left(\sum _{j=1}^{6}\sum _{i=1}^{n}W_{j}^{(i)}\cdot V_{i}^{(j)}\right)$

where:

$V_{i}^{(j)}$ is participant $i$ ’s vote at layer $j$ (either +1 for "yes" or -1 for "no").
$W_{j}^{(i)}$ is their weighted influence.

The decision passes if $O=+1$ , otherwise it is rejected.

Example Calculation

Consider three participants:

1. Participant A: 10 CUs, votes "yes" consistently. 2. Participant B: 5 CUs, switches from "no" to "yes." 3. Participant C: 3 CUs, votes "no" consistently.

Using senary scaling:

Participant A: $W_{A}=(1.0+10)\times S_{j}$
Participant B: $W_{B}=(1.0+5)\times S_{j}$ , with a 50% penalty for switching.
Participant C: $W_{C}=(1.0+3)\times S_{j}$

Total votes:

$O={\text{sign}}(12\cdot (+1)+4.5\cdot (+1)+4\cdot (-1))=+1$

The motion passes.

RE-L & Mycelith: Integrated Ethical Governance

Mycelith enforces RE-L at every step:

⭐ Voting is weighted by Contribution Units (CUs) – Prevents influence from speculative participants.
⭐ Ethical Violations Trigger Hyphen Node Reviews – Ensures that RE-L compliance is upheld.
⭐ Decisions are executed as Seigr Capsules – Provides cryptographic integrity and tamper resistance.

Conclusion

The Mycelith Voting System is an adaptive, ethical, and decentralized decision-making model designed for long-term sustainability, fairness, and transparency within Seigr. By linking voting weight directly to verified contributions, Mycelith prevents manipulation while ensuring fair representation for all engaged contributors.

Mycelith is the foundation of Seigr’s governance, ensuring that ethical, community-driven decisions shape the ecosystem’s evolution.

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 = Mycelith Voting System =
-The '''Mycelith Voting System''' is a decentralized, layered voting mechanism designed for the Seigr ecosystem. Inspired by the resilient and adaptive nature of mycelial networks, Mycelith empowers community-driven decision-making while promoting fairness, adaptability, and ethical governance. The system is engineered to accommodate participants’ evolving insights, rewarding consistency and commitment through a structured, multi-layered approach.
+The '''Mycelith Voting System''' is a decentralized, senary-based decision-making mechanism designed to ensure '''transparent, fair, and ethically governed voting''' within the Seigr ecosystem. Mycelith directly integrates with the [[Special:MyLanguage/Rebel Earthling License (RE-L)|Rebel Earthling License (RE-L)]] to '''enforce ethical compliance, track contributor influence, and uphold fair resource allocation.'''
-== Overview of Mycelith ==
+Mycelith is designed to be:
-The Mycelith Voting System is structured around sequential voting rounds, or '''layers''', that create a gradual decision-making process. Each layer increases the influence weight of votes cast, encouraging participants to engage consistently throughout the entire process. This layered structure aligns with Seigr’s ethos of transparency, resilience, and collaborative evolution, drawing on principles from biological networks that adapt to dynamic conditions.
+* '''Adaptive''' – Decisions evolve across six structured layers, mirroring the decentralized intelligence of mycelial networks.
+* '''Transparent''' – All votes are publicly auditable, and contributions are traceable via [[Special:MyLanguage/Contribution Units (CUs)|Contribution Units (CUs)]].
+* '''Resilient''' – Voting outcomes dynamically adjust based on long-term community engagement and commitment.
-=== Key Features ===
+== Mycelith & RE-L: Ethical Voting in Seigr ==
-. '''Senary-Scaled Voting Layers''': Mycelith operates on a six-layer voting system, each layer assigned a unique scaling factor based on Seigr’s senary (base-6) principles. This scaling rewards consistent participants by amplifying their influence across layers.
+Unlike traditional voting systems, Mycelith ensures that decisions:
-. '''Weighted Voting through WCAS''': Each participant’s influence in the system is weighted by their [[Special:MyLanguage/Weighted Consistency and Alignment Score (WCAS)|Weighted Consistency and Alignment Score (WCAS)]], which accounts for their experience, prior participation, and adherence to ethical standards within the ecosystem.
-. '''Adaptive Scaling''': Mycelith’s influence scaling increases with each layer, allowing participants who commit early and stay consistent to gain more influence. This design mirrors the adaptability of mycelial networks and enhances decision-making by valuing both immediate insights and reinforced decisions.
+* '''Are directly linked to Contribution Units (CUs)''' – A participant’s voting weight is proportional to their documented contributions.
+* '''Reinforce ethical licensing''' – Votes that contradict RE-L’s ethical compliance can be flagged by [[Special:MyLanguage/Hyphen Network|Hyphen Nodes]] for review.
+* '''Are governed by Seigr-Native enforcement''' – All Mycelith outcomes are executed via [[Special:MyLanguage/Seigr Capsules|Seigr Capsules]].
-The layered approach provides a nuanced decision-making model that encourages careful consideration, consistency, and adaptability, aligning closely with Seigr’s core principles.
+This ensures that voting power is '''earned through verifiable contributions''' rather than arbitrary social metrics.
-== Structure of the Mycelith Voting System ==
+== Six-Layer Voting Structure ==
-Mycelith’s voting process unfolds over six structured layers, denoted as <math>L_1</math> to <math>L_6</math>. Each layer provides an opportunity for participants to maintain or adjust their votes, with influence weights progressively increasing to reward consistent engagement.
+Mycelith is structured around '''six sequential voting layers''', where each layer increases the influence of consistent participants. Each layer (<math>L_1</math> to <math>L_6</math>) allows for '''vote refinement, discussion, and weighted commitment tracking.'''
-=== Six Voting Layers Explained ===
+{| class="wikitable"
+! Layer !! Description !! Influence Scaling
+|-
+| '''Layer 1 (Initiation)''' || Initial vote, minimal weight. || <math>S_1 = 1.0</math>
+|-
+| '''Layer 2 (Observation)''' || Minor weight increase; early revisions allowed. || <math>S_2 = 1.2</math>
+|-
+| '''Layer 3 (Consensus Building)''' || Influence increases as participants justify positions. || <math>S_3 = 1.44</math>
+|-
+| '''Layer 4 (Commitment Phase)''' || Higher weight to consistent votes; switching is penalized. || <math>S_4 = 1.728</math>
+|-
+| '''Layer 5 (Final Validation)''' || Near-max influence; Hyphen Nodes review integrity. || <math>S_5 = 2.0736</math>
+|-
+| '''Layer 6 (Execution Layer)''' || Decision is finalized and executed via Seigr Capsules. || <math>S_6 = 2.48832</math>
+|}
-The six layers are defined as follows:
+== Contribution-Based Voting Weight (CBVW) ==
-* '''Layer 1 (Initial)''': Participants cast an initial vote with minimal influence weight. This layer establishes the starting point for each voter’s stance.
+Each participant’s voting influence is '''directly linked to their Contribution Units (CUs)'''. This is measured by the '''Contribution-Based Voting Weight (CBVW)''', replacing the outdated WCAS system.
-* '''Layer 2 (Observation)''': Influence weight increases slightly, allowing participants to reaffirm or adjust their initial choice based on early trends.
-* '''Layers 3–6 (Commitment Layers)''': Influence weights increase significantly for participants who maintain their stance, with the highest weight applied in Layer 6. This progression rewards consistency, ensuring that committed participants’ votes have the most impact by the final layer.
-The progression of layers allows participants to refine their stance over time, encouraging thoughtful participation and providing a system that values both initial instincts and reinforced choices.
+Let:
-== Mathematical Model of Mycelith Voting ==
+* <math>V_i</math> be participant <math>i</math>’s base voting weight.
+* <math>W_i</math> be their weighted influence based on their Contribution Units.
-Mycelith employs a senary scaling model to calculate influence across layers. Influence increases exponentially with each layer, allowing for a dynamic scaling that prioritizes commitment and consistency.
+== Aggregating Votes for the Final Decision ==
-Let:
+The final vote outcome <math>O</math> is determined using senary influence scaling.
-* <math>W_i</math> represent the base influence of participant <math>i</math>, derived from their WCAS.
-* <math>S_j</math> denote the senary scaling factor for layer <math>j</math>.
-* <math>W_j^{(i)}</math> represent the influence weight of participant <math>i</math> in layer <math>j</math>.
-The scaling factor for each layer is computed as:
+Each participant’s weighted vote is calculated as:
-<math>
-S_j = 1.2^j
-</math>
-where <math>j = 1, 2, \ldots, 6</math>, representing each of the six layers. This exponential factor ensures that influence grows gradually and rewards participants who remain consistent.
-The influence of a participant in each layer is then given by:
 <math>
 W_j^{(i)} = W_i \cdot S_j
 </math>
-This model allows the influence of each participant to be adjusted according to their consistency and the progression of the voting layers.
+where:
-=== Consistency Adjustment ===
+* <math>W_i</math> is the participant's base weight.
+* <math>S_j</math> is the senary scaling factor at layer <math>j</math>.
-Participants who maintain their stance across all layers receive full influence, while those who switch incur a moderation factor, <math>\gamma</math>, applied to their influence in layers where they change. This adjustment rewards consistent voting behavior:
+Votes are aggregated using:
-* <math>\gamma</math> is a consistency factor where <math>0 < \gamma < 1</math>.
-* If a participant changes their vote between layers, their influence for that layer is reduced by <math>\gamma</math>.
-For example, if a participant’s influence for a layer would be <math>W_j^{(i)}</math>, but they switched their vote, their moderated influence becomes <math>\gamma \cdot W_j^{(i)}</math>.
-== Aggregating Votes for the Final Decision ==
-The final outcome <math>O</math> of a proposal is calculated by summing all influence-weighted votes across layers. Let <math>V^{(j)}_i</math> represent participant <math>i</math>’s vote in layer <math>j</math>, where <math>V^{(j)}_i \in \{ +1, -1 \}</math> for binary decisions ("yes" or "no").
-The outcome <math>O</math> is determined as follows:
 <math>
 O = \text{sign} \left( \sum_{j=1}^{6} \sum_{i=1}^{n} W_j^{(i)} \cdot V^{(j)}_i \right)
 </math>
 where:
-* <math>O = +1</math> indicates a "yes" outcome.
-* <math>O = -1</math> indicates a "no" outcome.
-This aggregated result reflects both the influence and consistency of participants, ensuring a fair and adaptive decision-making process.
+* <math>V^{(j)}_i</math> is participant <math>i</math>’s vote at layer <math>j</math> (either +1 for "yes" or -1 for "no").
+* <math>W_j^{(i)}</math> is their weighted influence.
+The decision passes if <math>O = +1</math>, otherwise it is rejected.
 === Example Calculation ===
-Consider three participants, A, B, and C, with WCAS-derived influence scores. Assume:
+Consider three participants:
-* '''Participant A''': <math>W = 0.7</math>, votes "yes" consistently.
+. '''Participant A''': 10 CUs, votes "yes" consistently.
-* '''Participant B''': <math>W = 0.5</math>, switches from "no" to "yes" mid-process.
+. '''Participant B''': 5 CUs, switches from "no" to "yes."
-* '''Participant C''': <math>W = 0.4</math>, votes "no" consistently.
+. '''Participant C''': 3 CUs, votes "no" consistently.
-The senary scaling factors <math>S_j</math> for each layer are:
+Using senary scaling:
-* <math>S_1 = 1.0</math>, <math>S_2 = 1.2</math>, <math>S_3 = 1.44</math>, <math>S_4 = 1.728</math>, <math>S_5 = 2.0736</math>, <math>S_6 = 2.48832</math>
-. '''Participant A''': Consistently "yes"
+* '''Participant A''': <math>W_A = (1.0 + 10) \times S_j</math>
-   <math>
+* '''Participant B''': <math>W_B = (1.0 + 5) \times S_j</math>, with a 50% penalty for switching.
-   \text{Total Influence}_A = 0.7 \times (1.0 + 1.2 + 1.44 + 1.728 + 2.0736 + 2.48832) = 7.236
+* '''Participant C''': <math>W_C = (1.0 + 3) \times S_j</math>
-   </math>
-. '''Participant B''': Switches from "no" to "yes"
+Total votes:
-   <math>
-   \text{Total Influence}_B = 0.5 \times (1.0 + 1.2 + 1.44) + 0.5 \times (1.728 + 2.0736 + 2.48832) \times 0.5 = 2.73
-   </math>
-. '''Participant C''': Consistently "no"
-   <math>
-   \text{Total Influence}_C = 0.4 \times (1.0 + 1.2 + 1.44 + 1.728 + 2.0736 + 2.48832) = 4.136
-   </math>
-Aggregated outcome:
 <math>
-O = \text{sign} (7.236 \cdot (+1) + 2.73 \cdot (+1) + 4.136 \cdot (-1)) = +1
+O = \text{sign} (12 \cdot (+1) + 4.5 \cdot (+1) + 4 \cdot (-1)) = +1
 </math>
-The outcome is "yes," reflecting the influence-weighted voting.
+The motion passes.
-== Summary of Senary Influence ==
+== RE-L & Mycelith: Integrated Ethical Governance ==
-By applying senary scaling, Mycelith ensures fair and adaptable voting, rewarding consistency and reflecting Seigr’s values of resilience, ethical governance, and community empowerment.
+Mycelith enforces RE-L at every step:
-== Further Reading ==
+* '''⭐ Voting is weighted by Contribution Units (CUs)''' – Prevents influence from speculative participants.
+* '''⭐ Ethical Violations Trigger Hyphen Node Reviews''' – Ensures that RE-L compliance is upheld.
+* '''⭐ Decisions are executed as Seigr Capsules''' – Provides cryptographic integrity and tamper resistance.
-For more details on related topics, refer to:
+== Conclusion ==
-* [[Special:MyLanguage/Weighted Consistency and Alignment Score (WCAS)|WCAS]]
-* [[Special:MyLanguage/Adaptive Replication|Adaptive Replication]]
+The '''Mycelith Voting System''' is an adaptive, ethical, and decentralized decision-making model designed for '''long-term sustainability, fairness, and transparency within Seigr.''' By linking voting weight directly to verified contributions, Mycelith prevents manipulation while ensuring '''fair representation for all engaged contributors.'''
-* [[Special:MyLanguage/Seigr Metadata|Seigr Metadata]]
-* [[Special:MyLanguage/Senary_(Base-6)|Senary]]
+''Mycelith is the foundation of Seigr’s governance, ensuring that ethical, community-driven decisions shape the ecosystem’s evolution.''
+== Explore Further ==
+* [[Special:MyLanguage/Rebel Earthling License (RE-L)|Rebel Earthling License (RE-L)]]
+* [[Special:MyLanguage/Contribution Units (CUs)|Contribution Units (CUs)]]
+* [[Special:MyLanguage/Hyphen Network|Hyphen Network]]
+* [[Special:MyLanguage/Seigr Capsules|Seigr Capsules]]
 * [[Special:MyLanguage/Seigr Protocol|Seigr Protocol]]
-The Mycelith Voting System is a powerful tool that combines mathematical rigor, ethical considerations, and decentralized principles, providing Seigr’s community with a fair and transparent method for collective decision-making.