Invisible Labor: The Backbone of Open Source Software
- URL: http://arxiv.org/abs/2503.13405v1
- Date: Mon, 17 Mar 2025 17:34:45 GMT
- Title: Invisible Labor: The Backbone of Open Source Software
- Authors: Robin A. Lange, Anna Gibson, Milo Z. Trujillo, Brooke Foucault Welles,
- Abstract summary: Open source software (OSS) is software that is viewable, editable and shareable by anyone with internet access.<n>We interviewed OSS contributors and asked them about their invisible labor contributions, leadership departure, membership turnover and sustainability.<n>We found that invisible labor is responsible for good leadership, reducing contributor turnover, and creating legitimacy for the project as an organization.
- Score: 0.9374652839580183
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Invisible labor is an intrinsic part of the modern workplace, and includes labor that is undervalued or unrecognized such as creating collaborative atmospheres. Open source software (OSS) is software that is viewable, editable and shareable by anyone with internet access. Contributors are mostly volunteers, who participate for personal edification and because they believe in the spirit of OSS rather than for employment. Volunteerism often leads to high personnel turnover, poor maintenance and inconsistent project management. This in turn, leads to a difficulty with sustainability long term. We believe that the key to sustainable management is the invisible labor that occurs behind the scenes. It is unclear how OSS contributors think about the invisible labor they perform or how that affects OSS sustainability. We interviewed OSS contributors and asked them about their invisible labor contributions, leadership departure, membership turnover and sustainability. We found that invisible labor is responsible for good leadership, reducing contributor turnover, and creating legitimacy for the project as an organization.
Related papers
- "Ohhh, He's the Boss!": Unpacking Power Dynamics Among Developers, Designers, and End-Users in FLOSS Usability [15.427821536893108]
We explore how power of different FLOSS stakeholders manifests and can be mediated during collaboration.
We conducted eight design workshops with different combinations of key FLOSS stakeholders.
Our results contribute to a comprehensive understanding of the power dynamics among FLOSS stakeholders.
arXiv Detail & Related papers (2025-04-21T23:52:03Z) - Sustaining Maintenance Labor for Healthy Open Source Software Projects through Human Infrastructure: A Maintainer Perspective [0.5188841610098436]
Open Source Software (OSS) fuels our global digital infrastructure but is commonly maintained by small groups of people.
Our study aims to investigate how maintenance labor can be supported and secured to enable the creation and maintenance of sustainable OSS projects.
arXiv Detail & Related papers (2024-08-13T08:30:52Z) - Unleashing Excellence through Inclusion: Navigating the Engagement-Performance Paradox [0.0]
People who feel that they do not belong (or their voice is not heard at work) commonly become disengaged, unproductive, and pessimistic.
This paper contributes to the literature on quality and performance management by developing a conceptual model of inclusion that directly impacts performance.
arXiv Detail & Related papers (2024-07-13T19:30:01Z) - WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks [85.95607119635102]
Large language models (LLMs) can mimic human-like intelligence.<n>WorkArena++ is designed to evaluate the planning, problem-solving, logical/arithmetic reasoning, retrieval, and contextual understanding abilities of web agents.
arXiv Detail & Related papers (2024-07-07T07:15:49Z) - GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications [46.85306320942487]
Large Language Models (LLMs) are evolving to actively engage with tools and performing actions on real-world applications and services.
Today, humans verify the correctness and appropriateness of the LLM-generated outputs before putting them into real-world execution.
This poses significant challenges as code comprehension is well known to be notoriously difficult.
In this paper, we study how humans can efficiently collaborate with, delegate to, and supervise autonomous LLMs in the future.
arXiv Detail & Related papers (2024-04-10T11:17:33Z) - Co-Supervised Learning: Improving Weak-to-Strong Generalization with
Hierarchical Mixture of Experts [81.37287967870589]
We propose to harness a diverse set of specialized teachers, instead of a single generalist one, that collectively supervises the strong student.
Our approach resembles the classical hierarchical mixture of experts, with two components tailored for co-supervision.
We validate the proposed method through visual recognition tasks on the OpenAI weak-to-strong benchmark and additional multi-domain datasets.
arXiv Detail & Related papers (2024-02-23T18:56:11Z) - Invisible Labor in Open Source Software Ecosystems [0.0]
Invisible labor is work that is either not fully visible or not appropriately compensated.<n>Our study shows that roughly half of open source software (OSS) work is invisible.<n>This could improve fairness in software development while providing greater transparency into work designs.
arXiv Detail & Related papers (2024-01-12T20:52:56Z) - Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration [116.09561564489799]
Solo Performance Prompting transforms a single LLM into a cognitive synergist by engaging in multi-turn self-collaboration with multiple personas.
A cognitive synergist is an intelligent agent that collaboratively combines multiple minds' strengths and knowledge to enhance problem-solving in complex tasks.
Our in-depth analysis shows that assigning multiple fine-grained personas in LLMs improves problem-solving abilities compared to using a single or fixed number of personas.
arXiv Detail & Related papers (2023-07-11T14:45:19Z) - Rethinking People Analytics With Inverse Transparency by Design [57.67333075002697]
We propose a new design approach for workforce analytics we refer to as inverse transparency by design.
We find that architectural changes are made without inhibiting core functionality.
We conclude that inverse transparency by design is a promising approach to realize accepted and responsible people analytics.
arXiv Detail & Related papers (2023-05-16T21:37:35Z) - Can Workers Meaningfully Consent to Workplace Wellbeing Technologies? [65.15780777033109]
This paper unpacks the challenges workers face when consenting to workplace wellbeing technologies.
We show how workers are vulnerable to "meaningless" consent as they may be subject to power dynamics that minimize their ability to withhold consent.
To meaningfully consent, participants wanted changes to the technology and to the policies and practices surrounding the technology.
arXiv Detail & Related papers (2023-03-13T16:15:07Z) - Leaving My Fingerprints: Motivations and Challenges of Contributing to
OSS for Social Good [17.145094780239564]
We conducted 21 semi-structured interviews with OSS for Social Good contributors.
We find that the majority of contributors demonstrate a distinction between OSS4SG and OSS.
OSS4SG contributors evaluate the owners of the project significantly more than OSS contributors.
arXiv Detail & Related papers (2021-04-26T21:50:11Z)
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.