User:Myclob

Personal Views

This user values reason over faith.

Proposal

We aim to launch political parties inspired by the transparent and collaborative model of Wikipedia. Distinct from conventional parties that may tailor facts to suit established narratives, our proposed entities will prioritize data. Our allegiance is to methodologies proven most effective through transparent, online cost/benefit analyses, edited collaboratively in a manner akin to Wikipedia entries. We plan to harness platforms like Wikipedia, alongside Blockchain technology and algorithms that elevate insightful ideas, to consistently illuminate the most advantageous courses of action.

Envisioning an E-Democracy represents a significant shift from our prevailing political landscape. As a step towards this ambitious goal, we propose the creation of a political party that embodies the principles of E-Democracy, applying its methodologies to enhance decision-making processes.

Rationale

Utilizing Wikipedia as a model for a pure direct democracy presents practical challenges. For instance, expecting every user to vote on each minor edit across the plethora of articles is unrealistic. Wikipedia's model, where individuals contribute when and where they can, enhances the platform's collective intelligence efficiently. Similarly, the idea of the public fully educating themselves on every issue and casting informed votes is not feasible. Following Wikipedia's example, we propose enabling individuals to contribute to our collective understanding of the best policy directions in a manageable way.

The concept of convening everyone in one place for a comprehensive, ongoing debate on every subject is not viable. The founders of democracy recognized this dilemma and introduced the system of elected representatives as a solution within their technological constraints.

Our proposal doesn't aim to replace representative democracy but to augment it. We advocate for the creation of political parties focused on data-driven decision-making. This approach offers a solid, practical pathway forward, combining the strengths of representative structures with the insights of a more engaged, informed electorate.

Methodology for the Idea Stock Exchange: A Detailed Overview

The Idea Stock Exchange introduces a groundbreaking methodology for discourse around policy-making, centered around evidence, transparency, and collaborative analysis. Here’s a refined look at its comprehensive methodology:

1. Structured Argumentation Framework:

Reasons to Support (Pro) and Oppose (Con): Arguments are systematically categorized into supporting and opposing sections, fostering a balanced assessment of each policy proposal. Dynamic Scoring System: Employs an algorithm to dynamically score arguments based on their evidence strength, relevance, and impact. This process encourages an evolving dialogue that adapts with new insights.

2. Comprehensive Costs and Benefits Analysis:

Multidimensional Evaluation: Undertakes a thorough analysis of costs and benefits across various dimensions such as financial, social, environmental, and health, to provide a holistic view of each policy's implications. Algorithmic Likelihood Calculations: An algorithm evaluates the likelihood of predicted outcomes by balancing supporting versus weakening evidence, ensuring a nuanced understanding of the policy's potential impacts.

3. Evidence-Based Arguments:

Robust Scientific Research: Gives precedence to high-quality scientific evidence, categorized by factors like sample size, randomization, and blinding procedures, ensuring the most reliable research informs the evaluation. Balanced Media Evaluation: Accounts for both supporting and weakening media sources, including scholarly articles, documentaries, and expert interviews, to present a comprehensive view of available evidence.

4. Logical and Ethical Reasoning:

Deductive and Ethical Analysis: Integrates logical deductions and ethical considerations, ensuring policies are not only viable but morally justified. Linkage and Unique Scoring: Arguments that support one another receive linkage scores to determine connection strength, along with unique scores to emphasize their distinct contribution. Unique scores are crucial for grouping similar arguments, reducing redundancy, and highlighting truly unique reasons to agree or disagree.

5. Continuous Improvement and Adaptation:

Open, Collaborative Editing: Inspired by platforms like Wikipedia, the Idea Stock Exchange encourages open editing of arguments and evidence, embracing the principles of collaborative e-democracy. Leveraging Technology: Incorporates advanced technologies like blockchain to enhance the transparency and integrity of the decision-making process.

6. Political Impact and Innovation:

Policy Influence: Aims to shape policy through evidence-based consensus, with the potential to influence the formation of new political entities or the direction of existing ones. Electoral Innovations: Promotes electoral reforms, such as ranked-choice voting and nonpartisan blanket primaries, to improve political processes for more equitable outcomes.

My apologies, you're right about the bolding format. Here's the revised version using instead of double square brackets:

What Next?

The roadmap ahead is not set in stone, and your collaboration is invaluable. What can you contribute? I have a wealth of ideas to share, and I invite you to explore them further through the following resources:

• GitHub Repository for ReasonRank: Dive into the technical details of the linkage score system and contribute to its development.
• The Idea Stock Exchange Blog: Discover insights and updates on our projects, and join the conversation on evolving the platform.
• Instagram Page: Get visual updates and engage with the community through comments and direct messages.
• Official Website of Idea Stock Exchange: Learn more about our mission, ongoing projects, and how you can get involved.
• Twitter Feed: Follow us for real-time updates, news, and interactive discussions.

Your insights, feedback, and contributions are what will shape the future of this platform. Let's collaborate to refine and evolve these ideas into tools that enhance our collective understanding and decision-making processes.

I hope this is the formatting you were looking for! Please let me know if you have any further questions.

Redefining Debate: Reasons to Agree and Disagree

My objective is to transform the process through which we arrive at conclusions and propagate our beliefs in arguments and politics. Essentially, the proposed format seeks to overcome the shortfalls of ineffective debates.

The model I propose places the belief at the top of a page, with a section for supporting arguments on one side and countering arguments on the other.

A wide range of elements can bolster a belief, including reasons, books, videos, individuals, songs, interests, and more. Utilizing crowdsourcing, efficient algorithms, and programming, we can create a system that attributes scores to elements supporting or countering a belief. The goal is to weigh the total points supporting a belief against the total points opposing it.

I have devised algorithms for each type of element that can support or counter a belief. For instance, users can list reasons to agree. Others can then rate these reasons on a scale of 1 to 10, based on the utilization of logical reasoning, verified data, etc. I find the comparison of the number of reasons to agree with a notion versus the number of reasons to disagree particularly intriguing. However, the quantity of reasons shared by an online community does not necessarily denote the quality of an idea. To address this, I have iterated my algorithm, enabling the repurposing of arguments and attributing individual scores to each reason. As a result, each argument holds a score, and ideas backed by a high number of robust arguments (and a low number of strong counterarguments) are deemed persuasive.

For instance, if you argue that we should establish wind farms in Wyoming, a supporting reason could be that wind energy in Wyoming is more cost-effective than coal. This secondary point would then be debated separately. If it's validated as true, its positive score would bolster the primary argument. Conversely, if it's debunked as false, its negative score would undermine the primary argument.

To delve deeper into this concept or to view illustrative examples, please refer to the following websites:

Additional Links

A forum I founded for enthusiasts intrigued by my idea. http://myclob.pbwiki.com/ I anticipated people would be attracted to engaging content and subsequently adopt the format. This content pertains to Mitt Romney, where I have attempted to utilize reasons to agree and disagree.

Favorites

Books

• David’s Sling by Marc Stiegler: This novel vividly envisions potential outcomes if my reasons-to-agree-and-disagree websites succeed.
• Deschooling Society by Ivan Illich: An eye-opening critique of conventional schooling, urging readers to question the status quo.
• Connecticut Yankee in King Arthur’s Court by Mark Twain: I have spent much of my life daydreaming about how I would assist in historical times, equipped with modern knowledge.
• I Robot by Isaac Asimov: A gripping narrative that departs significantly from the movie adaptation.
• One Billion Americans

Professional

This user is a licensed Professional Engineer in the U.S. State of Colorado.

This user qualifies as a nerd extraordinaire.

The Problem

Wikipedia brilliantly organizes factual knowledge with one page per topic. But online debate in the real world fails because we don't organize beliefs, arguments, and evidence the same way. Instead, arguments scatter across:

1. Thousands of disconnected forum posts
2. Chronologically-organized social media (where yesterday's insight disappears)
3. Duplicate debates repeating the same points year after year
4. Comment sections mixing 10 different claims in one thread

This means the same arguments get made repeatedly, evidence never accumulates, and we never actually resolve anything. The question is if the Wikipedia model (open source group efforts) can reform debates, and generate collective intelligence, before AI destroys us all.

The Solution: Wikipedia's Model Applied to Beliefs

Just as Wikipedia has one authoritative page for Alcohol (drug) organizing all factual knowledge, Wikidebate would have:

• Topic Pages: Organizing all beliefs about a topic (e.g., "Alcohol" topic page). We already have that on the main wikipedia page linking to related topics, but we would link to all the beliefs about a topic.

• Belief Pages: One page per distinct belief (e.g., "Alcohol causes more harm than benefit")

• Structured Pro/Con Arguments: Organized reasons to agree and disagree on the same page, grouped by different categories

Advanced Features that would require fancy code:

• Evidence Linking: Connections scores between claims and supporting/contradicting evidence, measuring the degree to which if the evidence were true it would necessarily strengthen the conclusion
• Automatic Scoring: Beliefs scored by the strength of their supporting arguments. I propose using PageRank, who's copyright has expired, and modifying it to count pro/con arguments and their sub-arguments (using linkage scores) similar to how Google counts links with PageRank. However, if we just had user edited tables with the top reasons to agree, and users moved them up and down the list arbitrarily (without real argument scores) it would be better better than biased pages that only have the pros/cons and never put them on the same page.

Example: How It Would Work for Alcohol

Why This Matters

Wikipedia succeeded because it recognized that scattered knowledge is useless knowledge. The same is true for arguments:

• Scattered Arguments = Progress Lost: The same points made over and over without building on previous work
• No Sorting = Talking Past Each Other: People argue different claims without realizing it
• Chronological Order Rewards Noise: Best argument from last year is invisible; loudest take today is front and center
• Topic Drift Enables Manipulation: Without fixed topics, easy to pivot to distractions

How It Would Work Technically

Building on Wikipedia's proven model:

• Collaborative Editing: Anyone can add arguments, evidence, or improvements
• Version Control: Full edit history like Wikipedia
• Dispute Resolution: Similar processes to Wikipedia's talk pages
• Advanced Options
• Algorithmic Scoring: Arguments scored based on supporting sub-arguments (like PageRank for reasoning)
• Neutrality Enforcement: Both pro and con arguments required; one-sided pages flagged
• Evidence Standards: Tiered quality scores based on methodology, replication, peer review

Differences from Wikipedia

Wikipedia focuses on neutral point of view with verifiable facts only, maintaining one truth per topic, with no original research, being descriptive (what is).

Wikidebate would organize all points of view systematically, including arguments, evidence, and logical connections, showing competing beliefs scored by argument strength, encouraging original argument synthesis (with evidence links), being evaluative (what follows from evidence).

Precedents and Related Work

Similar ideas have been attempted but never with Wikipedia's scale and governance model:

• Debategraph, Kialo, TruthMapping - small user bases, proprietary platforms
• Idea Stock Exchange (ISE) - open-source framework but needs institutional backing
• Various "argument mapping" tools - academic focus, not public-facing
• The Wikipedia Foundation's credibility, neutral governance, and proven collaborative model could succeed where others haven't.

Expected Objections and Responses

Objection 1: "This will become partisan and toxic"

Response: Wikipedia faced the same concern. Strong moderation policies, requirement for evidence, and structured format (not freeform comments) would prevent this. Both pro and con sections required on every page.

Objection 2: "Truth isn't democratic; we can't vote on facts"

Response: We're not voting on facts - we're organizing arguments and letting evidence quality determine scores algorithmically. Just as Google's PageRank doesn't "vote" on which websites are best but measures link structure, this would measure argument structure.

Objection 3: "This is too ambitious; Wikipedia took years to develop"

Response: Start small with pilot topics (climate change, vaccination, economic policy). Use existing open-source ISE framework as foundation. Scale gradually like Wikipedia did.

Objection 4: "Won't industry/governments manipulate this?"

Response: Same risk Wikipedia faces. Solutions: transparent edit logs, evidence quality standards, community oversight, flagging of conflicts of interest. Manipulation becomes visible and can be reverted.

Implementation Proposal

Phase 1 (6 months): Pilot with 10 controversial topics Develop belief and argument page templates Create evidence quality scoring system Build basic argument scoring algorithm Recruit initial editor community

Phase 2 (12 months): Expand to 100 topics Refine algorithms based on pilot feedback Develop automated duplicate detection Create cross-linking between related beliefs Establish moderation policies

Phase 3 (24 months): Public launch Integration with Wikipedia (links from factual articles to belief analysis) Mobile apps API for third-party tools Internationalization

Call to Action

The Wikipedia Foundation has already proven that collaborative knowledge organization works at global scale. Applying the same model to beliefs and arguments could:

Reduce repetitive debates by accumulating argument quality over time Make reasoning transparent and evidence-based Help people find common ground by identifying shared interests

Counter misinformation by linking claims directly to evidence Create collective intelligence infrastructure before AI makes human reasoning obsolete Wikipedia gave us one source of truth for facts. Wikidebate could give us one place to organize reasoning.

I propose the Wikipedia Foundation commission a feasibility study for this project. Myclob (talk) 00:14, 26 December 2025 (UTC)

Related Links

Idea Stock Exchange - Open Source Framework ) Wikipedia:Reliable sources - potential model for evidence tiers Wikipedia:Dispute resolution - applicable to argument disputes