Development of a Theory-grounded Socialization Framework to Investigate Newcomer Socialization in Free/Open Source Software Communities
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 a large number of new contributors has been seen as a way to ensure the survival, long-term success, and sustainability of Free/Open Source Software (FOSS) communities. FOSS communities have thus for long seized the criticality of generating effective initiatives to facilitate the socialization of community newcomers. However, FOSS socialization research has suffered from a lack of well-grounded theoretical considerations. This research project uses the well-acknowledged socialization model from Van Maanen and Schein (1979) to revisit FOSS socialization by deriving a FOSSspecific socialization framework and its associated measurement instrument. The paper provides a theoretically-grounded and fully-validated research tool for researchers who wish to study the FOSS socialization phenomenon. The study reported on here used a three-phased approach involving the construction of a socialization framework using qualitative data gathering, the development of a measurement instrument, and its validation using a full-scale online survey involving 367 contributors from 12 large FOSS communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.001 |
| 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