Jun 17, 2024
Introduction
On this report, we analyze the influence of the primary wave of KryptoCoinz’s Decentralized Voices (DV) program on the OpenGov panorama of Polkadot (foremost textual content) and Kusama (Appendix). Along with already accessible metrics (Dune), we make novel contributions in investigating the diploma to which delegate’s votes overlapped in addition to how voting energy (outlined when it comes to the Banzhaf energy index) distribution has modified with the DV program. Within the first a part of the report, we analyze the turnout, voting habits and settlement of DV delegates. After that, we zoom out and have a look in regards to the influence of the DV program on the voting energy distribution in OpenGov.
Our analyses reveal that the DV program has had a really constructive influence on OpenGov by amplifying the voices of delegates with various opinions and considerably contributing to a extra equitable distribution of voting energy.
What’s the Decentralized Voices program?
The Decentralized Voices program, initiated by the KryptoCoinz, goals to reinforce the decentralization of Polkadot by decentralizing its governance. Within the first cohort, this program delegated 7x 1M DOT at 6x conviction on Polkadot and 6x 5k KSM at 6x conviction on Kusama, though the variety of delegates has elevated to 10 on each Polkadot and Kusama for the second cohort. Within the first cohort, votes had been delegated on the 2 Tipper and three Spender tracks, though extra tracks had been added for Cohort 2.
The important thing motive for the Decentralized Voices is to permit passionate and educated contributors inside the ecosystem to develop their delegations and affect governance selections. The overarching aim of the DV program is to foster a extra inclusive and consultant decision-making course of inside the Polkadot and Kusama networks, thereby strengthening the general decentralization of the platforms.
Who’re the delegates?
Delegates within the DV program are chosen primarily based on standards resembling neighborhood involvement, previous voting exercise, and their potential to contribute positively to the ecosystem. The roster of delegates rotates each three months to make sure contemporary views and continued engagement. The primary roster included ChaosDAO, Jimmy Tudeski, Kukabi, Polkadotters, Polkaworld, Saxemberg, and William. Delegates are entrusted with important voting energy and are anticipated to signify a various vary of views and pursuits inside the Polkadot and Kusama communities. This structured strategy to delegate choice and rotation helps keep a dynamic and responsive governance framework.
Given the clear nature of the blockchain, we’re capable of intently observe the voting habits of the DV delegates. For this evaluation, we incorporate knowledge of Referenda 500 to 837 on Polkadot.
Turnout
In whole, there have been 326 referenda up for vote (of which 273 had been completed as of writing). ChaosDAO voted on virtually each referendum, whereas Kukabi and Saxemberg participated in >75% of referenda. On common, delegates voted in 67% of all completed referenda.
Voting Habits
Polkaworld confirmed the best Aye share at 78.3% (on a comparatively small pattern measurement in comparison with different DVs), whereas ChaosDAO had the best Nay share at 45.5%. General, DVs voted in a reasonably balanced method, with common Aye/Nay shares at 53.9% and 35.4%, respectively. Kukabi and William have forged the best share of Abstain votes, at 18.6% and 26.8% of the time, respectively.
Settlement between DV Delegates
On this paragraph, we analyze what number of delegates agreed with different delegates of their votes. This metric compares every delegate pairwise and calculates a rating of settlement. In essence, if two voters at all times voted the identical method (and voted), then their rating can be 100%. If two voters at all times voted in a different way (and voted), their rating can be 0%. Non-votes aren’t counted within the comparability. Since each delegate voted in a major quantity of referenda, every comparability contains sufficient knowledge factors to be significant. The diagonal (the settlement inside a delegate) is by definition 100% and, as an example that time, marked with “NA”.
The typical settlement between delegates is ~69%.
Controversial Referenda
On this paragraph, we delve right into a subset of referenda. Beforehand, we thought of all referenda, together with those who had been clearly accredited (resembling non-controversial runtime upgrades) or clearly rejected (like referenda with defective pre-images). These instances didn’t provide a lot perception into delegate opinions as a result of the outcomes had been clear-cut. Nonetheless, for a extra compelling evaluation, we now deal with the controversial referenda — these the place opinions various considerably. Particularly, we look at referenda with over 20% approval regardless of being rejected or beneath 80% approval regardless of being accepted. Whereas there is no such thing as a agreed-upon definition of a controversial referendum, these numbers strike us as a considerable portion of voters disagreed with the ultimate final result. Based on this standards, we recognized 85 controversial referenda in whole. The next desk supplies the entire votes of DV delegates in these referenda.
Turnout
By specializing in controversial referenda solely, the general turnout will increase in comparison with the earlier numbers, indicating that some delegates thought of not voting in referenda that had been already clearly accepted or rejected.
Vote instructions
Whereas the overall voting habits of most delegates aligns with their patterns in all referenda, ChaosDAO stands out as extra vital in these controversial instances. Their share of Nay votes will increase considerably, reaching 71.1%.
Voter Alignment
In comparison with the voter alignment in all referenda, the place the common was increased, the alignment in controversial referenda has dropped to round 50%. This lower is smart, on condition that controversial referenda inherently contain extra disagreement. It’s constructive to see this anticipated divergence play out among the many delegates. This vibrant mixture of opinions highlights how delegates are actively enriching the OpenGov panorama with their various views, making the method extra dynamic and consultant.
Voting Weight vs. Voting Energy
The best approach to analyze voter affect is to check the variety of (DOT) tokens or whole voting weights, with voting weights being the variety of tokens instances the conviction multiplier. This doesn’t, nevertheless, precisely signify the facility of a voter — take into account, for instance, the next scenario: whole token provide of 100, Alice has 49, Bob has 45, and Charlie has 6. A easy majority is required to win. Since every set of two voters achieves >51 of tokens to vote, all people’s energy is equal, regardless of their share holdings of the entire token provide various vastly.
On this evaluation, we use the Banzhaf energy index to research the facility buildings on the extremely lively Medium and Massive Spender tracks on Polkadot and examine the scenario earlier than versus after the introduction of the Decentralized Voices program. Snapshots had been taken on January 8, 2024 (earlier than DV) and June 3, 2024 (after DV) with a 90-day lookback interval for voting extrinsics and aggregated to outline an voters, which encompasses all at present lively OpenGov voters.
Medium Spender Observe
Earlier than the DV program was launched, the ten strongest voters had been:
The highest 3 strongest voters on the medium spender origin had been 14DN… with a voting weight of 33.75M DOT and a voting energy of 0.208; 16DG… with a voting weight of 30M DOT and a voting energy of 0.173; and 14zP… with a voting weight of 18M DOT and a voting energy of 0.104. Because of this, for instance, 14DN… was required in 20.8% of all profitable coalitions inside the Medium Spender voters of voting DOT holders.
The most effective case for small voters (<0.1% of whole voting weight every) of forming a coalition collectively would result in a complete voting weight of 8.53M DOT and a ensuing voting energy of 0.044, occupying spot no. 7 within the high 10 voters. General, the highest 10 voters would then maintain 77.7% of the entire voting energy, with the remainder, which means medium-sized voters exterior the highest 10, at 22.3%.
With the introduction of Decentralized Voices, the facility buildings modified significantly:
The overall voting weight on this monitor elevated from 175M DOT to 274M DOT, highlighting strongly elevated participation by DOT holders past the 42M DOT in voting weight added by way of the DV program. 15Qu… is now the biggest voter, with 15.5% of the entire weight and 17.4% voting energy. 15Qu… is separated from 16DG… by a single hop on-chain and thus probably the identical entity. General, the facility construction is extra balanced: Whereas the highest 3 voters held virtually 50% of the voting energy earlier than the DV program, they now maintain about 37%. The Decentralized Voices are sitting at ca. 2.2% voting energy per DV delegate, or ca. 15.5% in whole.
Voting Energy Distribution (Gini Coefficient and Lorenz Curve)
To realize a clearer understanding of the distribution of voting energy, we are able to use the Gini coefficient, a well-established measure of equality. The Gini coefficient, together with its graphical illustration by way of the Lorenz Curve, permits us to visualise how evenly voting energy is distributed amongst contributors. Basically, a decrease Gini coefficient signifies a extra equitable distribution of voting energy, suggesting that it’s unfold extra evenly throughout people. Conversely, a better Gini coefficient signifies higher focus of voting energy within the palms of fewer people, highlighting inequality within the distribution. Traditionally, the gini coefficient is commonly used to trace revenue or wealth inequality among the many inhabitants of nations. Given a current report of Credit score Suisse (2022), empirical observations vary from a minimal (best-case) of 0.51 to a most (worst-case) of 0.89. The world (weighted) common in 2022 was round 0.89, which is very unequal. With these numbers in thoughts, we are able to have a look at the Gini Coefficient of voting energy and its visible illustration, the Lorenz Curve. Right here, the cumulative share of voters is plotted in opposition to the cumulative share of voting energy. If voting energy was completely equally distributed to each voter, we’d observe a diagonal line. The bigger the “stomach” is, i.e., deviates from the superbly diagonal, the bigger the inequality.
Within the determine above, we are able to clearly see that the Decentralized Voices program has had a major and constructive impact on the distribution of voting energy. It is because it created a counter-weight to beforehand very robust voters, which meant that their relative share of voting energy decreased and was redistributed to beforehand (virtually) non-existent voters. Moreover, it motivated extra DOT holders to take part in OpenGov, or to extend their conviction.
Massive Spender Observe
On the Massive Spender monitor, earlier than the introduction of DV, the next energy construction was current:
Within the absence of 14DN…, the following largest voter 16DG… held much more energy. On the Massive Spender monitor, 16DG… held 34.7% of the entire voting weight, however 40.7% of the voting energy. The subsequent largest voters, 14zP… and 16Zw…, had voting weights of 18M DOT and 12.6M DOT, respectively, however each had 14.6% of the voting energy — every of them was sufficient to attain ca. 50% of all voting weight along with 16DG…. The highest 5 voters held 83% of all voting energy.
In comparison with Medium Spender, the adjustments within the energy construction after the introduction of Decentralized Voices had been even bigger on Massive Spender:
The overall voting weight elevated remarkably from 86M DOT to 362M DOT. Massive Spender has been a really lively monitor attracting excessive turnouts, resembling on referendum 684 (Chainalysis) or 714 (Interlay). General, the facility construction on Massive Spender now appears effectively distributed, with the highest 3 voters holding 28.6% of the voting energy (versus 70% earlier than the introduction of DVs). Decentralized Voices maintain about 1.7% voting energy every, or ca. 11.5% in whole.
The next determine plots the Lorenz Curve and states the respective Gini Coefficients.
Much more pronounced than on the medium spender monitor, right here we see an enormous enchancment when it comes to voting energy distribution and voter participation.
Want for Change
Since April 2024, Polkadot’s OpenGov has launched a brand new monitor labeled “Want for Change.” This monitor allows correct aggregation of DOT holders’ opinions utilizing OpenGov’s actual voting mechanism. Though the outcomes of those referenda don’t set off any speedy on-chain actions, they function priceless indicators for the neighborhood.
As a result of this monitor was launched after the launch of the Decentralized Voices (DV) program, there was no delegation on this monitor in wave 1. Thus, the evaluation doesn’t absolutely align with our deal with the influence of DV. Nonetheless, we nonetheless embrace this evaluation to know the present distribution on the monitor. This serves as a helpful baseline for comparability with wave 2 of DV, when this system will delegate to this monitor as effectively.
The next graph plots the Lorenz Curve, illustrating the present distribution of voting energy on the “Want for Change” monitor. This preliminary evaluation will assist us later consider how wave 2 impacts the distribution.
Conclusion
The Decentralized Voices (DV) program has had a notably constructive influence on the OpenGov panorama of Polkadot and Kusama. This system has seen important voting turnout amongst delegates, with a median participation charge of 67% throughout all completed referenda, and a few delegates like ChaosDAO taking part in almost each referendum. The presence of DV delegates has been particularly influential in controversial referenda, usually swaying outcomes in vital votes. The voting habits amongst DV delegates is various, showcasing a balanced mixture of Aye, Nay, and Abstain votes, which helps signify a broad spectrum of neighborhood opinions. Importantly, the introduction of the DV program has led to a extra equitable distribution of voting energy. Previous to this system, the highest three voters on the Medium Spender monitor held almost 50% of the voting energy, a determine that has since decreased to about 37%. Equally, on the Massive Spender monitor, the facility held by the highest three voters dropped from 70% to twenty-eight.6%. The overall voting weight on each tracks has additionally elevated considerably, highlighting higher participation by DOT holders past the extra weight introduced in by the DV program.
General, the initiative has enhanced the inclusivity and representativeness of the decision-making course of inside the Polkadot and Kusama networks. The ability distribution has turn out to be extra balanced, as indicated by a considerably decrease Gini coefficient. Whereas the DV program has markedly improved the on-chain metrics for Polkadot’s OpenGov course of, you will need to acknowledge that off-chain discourse stays an important part of governance. Even smaller neighborhood members can affect bigger voters by way of considerate discussions and thorough analyses, underscoring the multifaceted nature of decentralized governance.
Particular Thanks
We’d wish to thank the Parity Knowledge crew for offering a part of the information for this report leveraging their infrastructure DotLake. The Parity Knowledge crew, now a part of the Parity Infra/Knowledge division, is pleased to help any ecosystem initiative, evaluation or analysis with knowledge entry or exports. For extra particulars, please consult with the next Polkadot Wiki web page: https://wiki.polkadot.community/docs/parity-data-dashboards.
Kusama, Polkadot’s “canary community”, additionally had its personal model of the Decentralized Voices program. Because the variety of Referenda is way smaller on Kusama, evaluation is rather more troublesome and values will likely be extra variable. For the sake of completeness, the information and restricted evaluation is included on this appendix.
Voting Habits
Turnout
Whole variety of referenda was 51.
Vote Course
Vote Alignment (solely controversial referenda)
Voting Energy
Medium Spender: PreDV
Medium Spender: PostDV
Medium Spender: Gini & Lorenz
On the Medium Spender monitor on Kusama, voting energy has already been effectively distributed between voters, as illustrated by the low Gini coefficient of 0.51. This stays true additionally after the introduction of Decentralized Voices, with a Gini coefficient of 0.55. Every DV had a voting energy of ca. 4%.
Massive Spender: PreDV
Massive Spender: PostDV
Massive Spender: Gini & Lorenz
Noteworthy for the Massive Spender monitor on Kusama is particularly the a lot elevated voting weight, from ~1.0M KSM pre-DV to ~1.8M KSM post-DV, exceeding the 240k KSM voting weight added immediately by way of the DV program. Accountable for this improve was principally the excessive turnout for referendum 377 (Subscan). As seen on the Medium Spender monitor, the Gini coefficient is low each earlier than and after the introduction of DVs. Every DV had a voting energy of ca. 1.7%, similar to the voting energy of DVs on Polkadot’s (extremely contested) Massive Spender monitor.