Contributors’ Withdrawal from Online Collaborative Communities: The Case of OpenStreetMap
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
Online collaborative communities are now ubiquitous. Identifying the nature of the events that drive contributors to withdraw from a project is of prime importance to ensure the sustainability of those communities. Previous studies used ad hoc criteria to identify withdrawn contributors, preventing comparisons between results and introducing interpretation biases. This paper compares different methods to identify withdrawn contributors, proposing a probabilistic approach. Withdrawals from the OpenStreetMap (OSM) community are investigated using time series and survival analyses. Survival analysis revealed that participants’ withdrawal pattern compares with the life cycles studied in reliability engineering. For OSM contributors, this life cycle would translate into three phases: “evaluation,” “engagement” and “detachment.” Time series analysis, when compared with the different events that may have affected the motivation of OSM participants over time, showed that an internal conflict about a license change was related to largest bursts of withdrawals in the history of the OSM project. This paper not only illustrates a formal approach to assess withdrawals from online communities, but also sheds new light on contributors’ behavior, their life cycle, and events that may affect the length of their participation in such project.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.009 |
| 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