Governance in Practice: How Open Source Projects Define and Document Roles
- URL: http://arxiv.org/abs/2603.24879v1
- Date: Wed, 25 Mar 2026 23:50:27 GMT
- Title: Governance in Practice: How Open Source Projects Define and Document Roles
- Abstract summary: Open source software (OSS) sustainability depends not only on code contributions but also on governance structures that define who decides, who acts, and how responsibility is distributed.<n>This paper investigates how OSS projects define and structure governance through their GOVERNANCE.md files and related documents.
- Score: 11.213029205609146
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Open source software (OSS) sustainability depends not only on code contributions but also on governance structures that define who decides, who acts, and how responsibility is distributed. We lack systematic empirical evidence of how projects formally codify roles and authority in written artifacts. This paper investigates how OSS projects define and structure governance through their GOVERNANCE.md files and related documents. We analyze governance as an institutional infrastructure, a set of explicit rules that shape participation, decision rights, and community memory. We used Institutional Grammar to extract and formalize role definitions from repositories hosted on GitHub. We decompose each role into scope, privileges, obligations, and life-cycle rules to compare role structures across communities. Our results show that although OSS projects use a stable set of titles, identical titles carry different responsibilities, and different labels describe similar functions, which we call role drift. Still, we observed that a few actors sometimes accumulate technical, managerial, and community duties. %This creates the Maintainer Paradox: those who enable broad participation simultaneously become governance bottlenecks. By understanding authority and responsibilities in OSS, our findings inform researchers and practitioners on the importance of designing clearer roles, distributing work, and reducing leadership overload to support healthier and more sustainable communities.
Related papers
- From Collaboration to Regulation: Characterizing Governance Practice in Three Deep Learning Open Source Communities [12.4881762708727]
Collaboration in Open Source Software (OSS) projects creates substantial coordination and quality-control challenges.<n>Project maintainers have limited systematic guidance on what rules to codify, when to introduce or revise them, and how to organize them across documents.<n>We analyzed 109 documents and identified 17 rule themes across seven rule types.
arXiv Detail & Related papers (2026-07-21T12:13:20Z) - The Granularity Axis: A Micro-to-Macro Latent Direction for Social Roles in Language Models [61.32031248060941]
We show that large language models encode social roles, from micro-level individual experience to macro-level organizational, institutional, or national reasoning.<n>Our findings suggest that social role granularity is not merely a stylistic surface feature, but a structured, ordered, and causally manipulable latent direction in language model behavior.
arXiv Detail & Related papers (2026-05-07T13:08:19Z) - How Do Ports Organise Innovation? Linking Port Governance, Ownership, and Living Labs [36.94429692322632]
Port studies rarely examine how ownership and decision rights shape the process and outcomes of sustainability and digital pilots.<n>Living Lab (LL) scholarship offers strong concepts, but limited sector-grounded explanation of LL-governance fit in ports.<n>We develop and apply a governance-LL fit framework linking port governance and ownership to four LL pillars: co-creation, real-life setting, iterative learning, and institutional embedding.
arXiv Detail & Related papers (2026-01-11T12:35:17Z) - A Human Behavioral Baseline for Collective Governance in Software Projects [12.47967674379491]
We study how open source communities describe participation and control through version controlled governance documents.<n>Using a corpus of 710 projects with paired snapshots, we parse text into actors, rules, actions, and objects, then group them and measure change with entropy for evenness, richness for diversity, and Jensen Shannon divergence for drift.
arXiv Detail & Related papers (2025-10-10T03:04:46Z) - Patterns in the Transition From Founder-Leadership to Community Governance of Open Source [12.47967674379491]
We analyze 637 GitHub repositories to trace transitions from founder-led to shared governance.<n>We find roles and actions grow, and regulation becomes more balanced.
arXiv Detail & Related papers (2025-09-19T15:55:08Z) - Modeling Motivated Reasoning in Law: Evaluating Strategic Role Conditioning in LLM Summarization [44.55119228567464]
Large Language Models (LLMs) are increasingly used to generate user-tailored summaries.<n>This raises important questions about motivated reasoning.<n>We investigate how LLMs respond to prompts conditioned on different legal roles.
arXiv Detail & Related papers (2025-08-30T15:22:47Z) - Toward a Theory of Agents as Tool-Use Decision-Makers [89.26889709510242]
We argue that true autonomy requires agents to be grounded in a coherent epistemic framework that governs what they know, what they need to know, and how to acquire that knowledge efficiently.<n>We propose a unified theory that treats internal reasoning and external actions as equivalent epistemic tools, enabling agents to systematically coordinate introspection and interaction.<n>This perspective shifts the design of agents from mere action executors to knowledge-driven intelligence systems, offering a principled path toward building foundation agents capable of adaptive, efficient, and goal-directed behavior.
arXiv Detail & Related papers (2025-06-01T07:52:16Z) - Control Illusion: The Failure of Instruction Hierarchies in Large Language Models [46.5792253691152]
Large language models (LLMs) are increasingly deployed with hierarchical instruction schemes.<n>We introduce a systematic evaluation framework based on constraint prioritization to assess how well LLMs enforce instruction hierarchies.
arXiv Detail & Related papers (2025-02-21T04:51:37Z) - Do Responsible AI Artifacts Advance Stakeholder Goals? Four Key Barriers Perceived by Legal and Civil Stakeholders [59.17981603969404]
The responsible AI (RAI) community has introduced numerous processes and artifacts to facilitate transparency and support the governance of AI systems.
We conduct semi-structured interviews with 19 government, legal, and civil society stakeholders who inform policy and advocacy around responsible AI efforts.
We organize these beliefs into four barriers that help explain how RAI artifacts may (inadvertently) reconfigure power relations across civil society, government, and industry.
arXiv Detail & Related papers (2024-08-22T00:14:37Z) - Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning [54.69189620971405]
We provide a unified framework, termed Identifiable Exchangeable Mechanisms (IEM), for representation and structure learning.<n>IEM provides new insights that let us relax the necessary conditions for causal structure identification in exchangeable non-i.i.d. data.<n>We also demonstrate the existence of a duality condition in identifiable representation learning, leading to new identifiability results.
arXiv Detail & Related papers (2024-06-20T13:30:25Z) - How to Gain Commit Rights in Modern Top Open Source Communities? [14.72524623433377]
We study the policies and practical implementations of committer qualifications in modern top OSS communities.
We construct a taxonomy of committer qualifications, consisting of 26 codes categorized into nine themes.
We find that the probability of gaining commit rights decreases as participation time passes.
arXiv Detail & Related papers (2024-05-03T01:23:06Z) - Towards Responsible AI in Banking: Addressing Bias for Fair
Decision-Making [69.44075077934914]
"Responsible AI" emphasizes the critical nature of addressing biases within the development of a corporate culture.
This thesis is structured around three fundamental pillars: understanding bias, mitigating bias, and accounting for bias.
In line with open-source principles, we have released Bias On Demand and FairView as accessible Python packages.
arXiv Detail & Related papers (2024-01-13T14:07:09Z) - Causal Fairness Analysis [68.12191782657437]
We introduce a framework for understanding, modeling, and possibly solving issues of fairness in decision-making settings.
The main insight of our approach will be to link the quantification of the disparities present on the observed data with the underlying, and often unobserved, collection of causal mechanisms.
Our effort culminates in the Fairness Map, which is the first systematic attempt to organize and explain the relationship between different criteria found in the literature.
arXiv Detail & Related papers (2022-07-23T01:06:34Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.