Abstract

A multitude of societal issues associated with the development of technology have emerged over the years including, but not limited to: insufficient personnel for maintenance; a lack of accessibility; the spread of harmful tools; and bias and discrimination against marginalized groups. I propose that a systems perspective is necessary to identify potential leverage points in technology production systems to influence them towards increased social good and evaluate their effectiveness for intervention. Toward this end, I conducted a mixed-methods study of a widely-adopted approach in tech production, free/libre and open source software (FLOSS) development. A survey was distributed to elicit responses from FLOSS project contributors to characterize their perceptions of diversity and corporate involvement as they relate to participation decisions and information gathering activities in online platforms. To complement this, an analysis of data from FLOSS projects on GitHub was completed to model participation dynamics. Survey results indicate that contributors attend to information that is used to infer group diversity and information about corporate decision making related to FLOSS systems. Furthermore, the influence of this information on participation decisions varies on the basis of economic needs and sociopolitical beliefs. Analyses of eighteen project ecosystems, with over 9,000 contributors, reveal that projects with no to some corporate involvement generally have broader contributor and user bases than those that are owned by a company. Taken together, these findings suggest that the internal practices of companies involved in FLOSS can be perceived as opaque and controlling which is detrimental to both the expansion of a project's contributor base and for increasing diversity across FLOSS ecosystems. This research highlights the need to differentiate projects on the basis of corporate involvement and community ethos to design appropriate interventions. A set of recommendations and research propositions are offered to improve inclusivity, equity, and sustainability in tech development.

Notes

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Graduation Date

2022

Semester

Fall

Advisor

Fiore, Stephen

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

School of Modeling, Simulation, and Training

Degree Program

Modeling & Simulation

Identifier

CFE0009833; DP0027774

URL

https://purls.library.ucf.edu/go/DP0027774

Language

English

Release Date

June 2023

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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