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 This is measured by the Contribution-Based Voting Weight (CBVW), replacing the outdated WCAS system.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 voting mechanism created for the Seigr ecosystem. Inspired by the interconnected and resilient nature of mycelium, the system aims to empower participants to vote on proposals fairly and transparently, while providing an adaptive, multi-layered approach to voting.
+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.'''
-== Introduction to Mycelith ==
+Mycelith is designed to be:
-In the Mycelith Voting System, proposals go through a series of voting rounds called '''layers'''. This multi-layered structure encourages participants to engage in decision-making gradually, with each layer adding additional influence based on participants' consistency and commitment to their initial vote.
+* '''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-Based Voting Layers''': The voting process is divided into six sequential layers, each increasing in influence weight. This means early voters who are consistent across layers gain more influence, while those who switch their votes have their influence moderated.
+Unlike traditional voting systems, Mycelith ensures that decisions:
-. '''Weighted Voting''': Each participant’s influence in voting is weighted by their commitment, experience, and consistency within the ecosystem, forming a dynamic influence score known as the [[Special:MyLanguage/Weighted Consistency and Alignment Score (WCAS)|WCAS]].
+* '''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]].
-. '''Adaptive Scaling''': The system incorporates a senary (base-6) scaling approach that reflects Seigr’s alignment with efficiency and sustainability. This senary structure shapes how influence is calculated across the six layers.
+This ensures that voting power is '''earned through verifiable contributions''' rather than arbitrary social metrics.
-This layered approach results in a more nuanced decision-making process, allowing participants to reflect and adjust their votes based on evolving insights, while incentivizing early, consistent voting behavior.
+== Six-Layer Voting Structure ==
-== Structure of the Mycelith Voting System ==
+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.'''
-The voting process in Mycelith is broken down into six layers, each representing a phase in the decision-making process. Each layer offers a chance for participants to either maintain their original vote or adjust it based on the previous results.
+{| 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 Voting Layers ===
+== Contribution-Based Voting Weight (CBVW) ==
-The six layers, represented as <math>L_1</math> through <math>L_6</math>, function as follows:
+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 1 (Initial)''': Participants cast an initial vote with minimal influence weight.
+Let:
-* '''Layer 2 (Observation)''': Influence slightly increases for participants who either maintain their stance or join the vote based on the results of Layer 1.
-* '''Layers 3-6 (Commitment Phases)''': Influence weights increase for participants who reinforce their commitment to their initial choice, with the highest influence weight reached in Layer 6.
-This progression allows voters to observe early trends before deepening their commitment, creating a system that values both initial opinions and refined decisions.
+* <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.
-== Mathematical Foundations ==
+== Aggregating Votes for the Final Decision ==
-Mycelith’s influence is calculated using a '''senary-based scaling system''', where influence is increased in each layer according to senary principles. This scaling ensures that consistent voting has a higher influence over time, while participants who switch their votes incur influence adjustments.
+The final vote outcome <math>O</math> is determined using senary influence scaling.
-Let:
+Each participant’s weighted vote is calculated as:
-* <math>W_j^{(i)}</math> denote the influence weight of participant <math>i</math> in layer <math>j</math>.
-* <math>W_i</math> represent the base influence of participant <math>i</math>, derived from their WCAS.
-* <math>S_j</math> be the senary scaling factor for each layer.
-The scaling factor <math>S_j</math> is calculated as:
-<math>
-S_j = 1.2^j
-</math>
-where <math>j = 1, 2, \ldots, 6</math> represents each layer. This exponential factor ensures influence grows gradually, providing a solid base for consistent participants.
-=== Influence Weight Calculation ===
-The influence of a participant in each layer is determined as follows:
 <math>
 W_j^{(i)} = W_i \cdot S_j
 </math>
-This calculation ensures that participants with a higher WCAS start with more influence, which is then amplified or moderated across the layers.
+where:
-== Consistency Reward and Weighted Voting ==
-Participants who maintain consistency in their voting stance across layers are rewarded with increasing influence, while those who switch votes have their influence moderated. This is achieved through an adjustment factor <math>\gamma</math> applied to participants who switch their vote.
+* <math>W_i</math> is the participant's base weight.
+* <math>S_j</math> is the senary scaling factor at layer <math>j</math>.
-* If a participant maintains the same vote in all layers, their influence is maximized.
+Votes are aggregated using:
-* If a participant switches, their influence in layers where they changed is reduced by a factor <math>\gamma</math>, where <math>0 < \gamma < 1</math>.
-This consistency mechanism rewards participants who commit to their original stance while allowing flexibility for others to change their decision with adjusted influence.
-== Calculation of the Voting Outcome ==
-The final outcome <math>O</math> of a proposal is determined by aggregating 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 a binary decision.
-The final outcome <math>O</math> is calculated as:
 <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.
-=== Example Scenario ===
+* <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.
-Consider three participants (A, B, and C) with WCAS-derived base influence scores:
+The decision passes if <math>O = +1</math>, otherwise it is rejected.
-* '''Participant A''': <math>W = 0.7</math>, votes "yes" consistently.
+=== Example Calculation ===
-* '''Participant B''': <math>W = 0.5</math>, changes vote from "no" to "yes" mid-process.
-* '''Participant C''': <math>W = 0.4</math>, votes "no" consistently.
-The senary scaling factors for each layer <math>S_j</math> are:
+Consider three participants:
-* <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>
-The total influence for each participant is calculated as follows:
+. '''Participant A''': 10 CUs, votes "yes" consistently.
+. '''Participant B''': 5 CUs, switches from "no" to "yes."
+. '''Participant C''': 3 CUs, votes "no" consistently.
-. '''Participant A (consistent "yes")''':
+Using senary scaling:
-   <math>
-   \text{Total Influence}_A = 0.7 \times (1.0 + 1.2 + 1.44 + 1.728 + 2.0736 + 2.48832) = 7.236
-   </math>
-. '''Participant B (switches from "no" to "yes")''':
+* '''Participant A''': <math>W_A = (1.0 + 10) \times S_j</math>
-   - Layers 1-3: "no" votes.
+* '''Participant B''': <math>W_B = (1.0 + 5) \times S_j</math>, with a 50% penalty for switching.
-   - Layers 4-6: "yes" votes, reduced by <math>\gamma = 0.5</math>.
+* '''Participant C''': <math>W_C = (1.0 + 3) \times S_j</math>
-   <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 (consistent "no")''':
+Total votes:
-   <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>
-indicating a "yes" outcome.
-== Senary Influence Summary ==
+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.'''
-By applying a senary scaling system, Mycelith provides an adaptive, fair voting process that rewards consistency while allowing participants flexibility. The senary influence structure gives balanced weight across each phase, aligning with Seigr’s commitment to transparency and ethical governance.
+''Mycelith is the foundation of Seigr’s governance, ensuring that ethical, community-driven decisions shape the ecosystem’s evolution.''
-== Further Reading ==
+== Explore Further ==
-For more information, see:
+* [[Special:MyLanguage/Rebel Earthling License (RE-L)|Rebel Earthling License (RE-L)]]
-* [[Special:MyLanguage/Weighted Consistency and Alignment Score (WCAS)|WCAS]]
+* [[Special:MyLanguage/Contribution Units (CUs)|Contribution Units (CUs)]]
-* [[Special:MyLanguage/Adaptive Replication|Adaptive Replication]]
+* [[Special:MyLanguage/Hyphen Network|Hyphen Network]]
-* [[Special:MyLanguage/Seigr Metadata|Seigr Metadata]]
+* [[Special:MyLanguage/Seigr Capsules|Seigr Capsules]]
-* [[Special:MyLanguage/Senary_(Base-6)|Senary]]
 * [[Special:MyLanguage/Seigr Protocol|Seigr Protocol]]