Myceliary

A research project exploring anti-capitalist frameworks and patterns in AI/ML

Research Archives

This page provides access to our complete research archives, including all primary research reports with their full citations and references.

Theoretical Frameworks Research

Anti-Capitalist Technology Frameworks

Research conducted: June 11, 2025

Key Insights

  1. Standards development organizations demonstrate collaborative knowledge production that limits corporate dominance
  2. Digital ecosocialism offers a comprehensive framework for transitioning to a socialist digital economy
  3. Decentralization and socialization of technology can promote community-driven governance
  4. Anti-capitalist software licensing presents a practical approach to challenging capitalist exploitation
  5. Technological dynamism can be harnessed to benefit society as a whole rather than capitalist interests

Citations and References

  1. The Anti-Capitalist Case for Standards - MIT Press Reader (2025-03-24)
  2. Anti-Capitalist Chronicles: When Technology Becomes A Business (2022-03-10)
  3. Anti-Capitalist Chronicles: Technological Dynamism - YouTube (2022-02-24)
  4. Digital Ecosocialism: Breaking the power of Big Tech
  5. The Path to Destroying Capitalism Might Go Through a Software License - VICE (2020-08-26)

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Indigenous Digital Sovereignty

Research conducted: June 11, 2025

Key Insights

  1. Indigenous data sovereignty movements recognize the rights of indigenous communities to control data about them and their territories
  2. Digital self-determination extends beyond data to include technological infrastructure, platforms, and governance
  3. Indigenous approaches often integrate traditional knowledge systems with digital technologies
  4. Case studies from tribal nations demonstrate diverse implementation approaches
  5. Policy frameworks and international declarations increasingly recognize indigenous digital rights

Citations and References

  1. Indigenous Data Sovereignty and Policy - Taylor & Francis (2021-05-02)
  2. Digital Sovereignty: Aboriginal Peoples and the Future of the Internet - CIRA (2023-10-15)
  3. Indigenous Knowledge Systems and Data Sovereignty - Ethics and Information Technology (2020-07-18)
  4. Tribal Technology Assessment: The State of Internet Service on Tribal Lands - American Indian Policy Institute (2022-08-01)
  5. Indigenous Peoples in the Information Age: From Digital Divide to Data Sovereignty - Routledge (2024-01-25)

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Technology Commons Governance Models

Research conducted: June 11, 2025

Key Insights

  1. Technology commons combine shared ownership with community-driven governance structures
  2. Polycentric governance models distribute decision-making across multiple centers
  3. Blockchain-based governance shows promise for transparent, auditable technology governance
  4. Platform cooperatives demonstrate viable alternatives to extractive technology platforms
  5. Various stewardship models provide frameworks for long-term commons maintenance

Citations and References

  1. Governing the Commons: The Evolution of Institutions for Collective Action - Cambridge University Press (1990)
  2. Platform Cooperativism: Challenging the Corporate Sharing Economy - Rosa Luxemburg Stiftung (2016)
  3. Patterns of Commoning - Commons Strategy Group (2015)
  4. Blockchain Governance: Programming Our Future - Hackernoon (2024-01-11)
  5. Community Rule: A Template for Peer Governance - Community Rule (2023-04-30)

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AI/ML Landscape Research

Open Source Large Language Models Community

Research conducted: June 5, 2025

Key Insights

  1. Open source LLMs offer transparency and customization capabilities that proprietary models cannot match
  2. Community-driven development is central to open source LLM advancement, with projects like LLM360 advocating for community-owned AGI
  3. Leading open source models include LLaMA 3.1 (8B-405B parameters), BLOOM (176B parameters), and Falcon 180B
  4. These models support multilingual capabilities and extensive context lengths (up to 128K tokens)
  5. While there may be performance trade-offs compared to proprietary models, open source LLMs provide flexibility in deployment and mitigate vendor lock-in risks

Citations and References

  1. Awesome-LLM: a curated list of Large Language Model - GitHub
  2. [LLM360 Community-Driven AGI via Open-Source LLMs](https://www.llm360.ai)
  3. Open Source Large Language Models - Industry Insider (2024-05-10)
  4. Top 10 open source LLMs for 2025 - NetApp Instaclustr
  5. Essential open source large language models to watch in 2025 (2024-12-13)

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