Value Tensions in OpenStreetMap: Openness, Membership, and Policy in Online Communities
Bibliographic record
Abstract
The social life and long-term trajectories of online peer production communities are shaped and animated in part by value tensions that arise when distributed, heterogeneous participants are brought together into collaboration. This study of OpenStreetMap (OSM) draws upon values-based approaches to investigate how peer production communities enact their values and navigate tensions between them. We examine how conflicts within the community over the rise of corporate participation in OSM provided a stage for the articulation and enactment of community values, shedding light on the broader dynamics and trajectory of the platform and its participants. The contributions of this work include reflections on how increasing corporate participation in OSM intersects with discourses about the emancipatory potential of emerging mapping technologies, insights into the challenges of scaling membership in peer production communities, and exploring the role of values in understanding the social life and governance of online communities.
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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 | 0.018 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.033 |
| Scholarly communication | 0.019 | 0.030 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".