Understanding Contributor Behavior within Large Free/Open Source Software Projects: A Socialization Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Attracting new contributors is a necessary but not a sufficient condition, to ensure the survival and long-term success of Free/ Open Source Software (FOSS) projects. The well-being of a FOSS project also depends on contributors performing behaviors that nurture the project and its associated community. This study is a quantitative investigation of the socialization factors that influence contributor performance in large FOSS projects. A conceptual model was developed and empirically examined with 367 contributors from 12 large FOSS projects. The model hypothesizes the mediating effect of two proximal socialization variables, social identification and social integration, between newcomer socialization and contributor performance (conceptualized as task performance and community citizenship behaviors). The results demonstrate the influence of social identification and social integration in predicting contributor performance, as well as the importance of key socialization factors that are: task segregation, task purposefulness, interaction intensity and supportiveness. Theoretical and practical implications are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it