Untold Stories: Unveiling the Scarce Contributions of UX Professionals to Usability Issue Discussions of Open Source Software Projects
Bibliographic record
Abstract
Previous work established that open source software (OSS) projects can benefit from the involvement of UX professionals, who offer user-centric perspectives and contributions to improve software usability. However, their participation in OSS issue discussions (places where design and implementation decisions are often made) is relatively scarce since those platforms are created with a developer-centric mindset. Analyzing a dataset sampled from five OSS projects, this study identifies UX professionals' distinct approaches to raising and following up on usability issues. Compared to other contributors, UX professionals addressed a broader range of usability issues, well-supported their stances, and were more factual than emotional. They also actively engage in discussions to provide additional insights and clarifications in comments following up on the issues they posted. Results from this study provide useful insights for increasing UX professionals' involvement in OSS communities to improve usability and end-user satisfaction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".