Intellectual Property Rights in Open Source Software Communities
Bibliographic record
Abstract
Intellectual property is an old concept, with the first recorded instances of patents (1449) and copyrights (1662) both occurring in England (“Intellectual property”, Wikipedia, 2004). The first piece of software was submitted for copyright to the United States Copyright Office in 1961, and was accepted as copyrightable under existing copyright law (Hollaar, 2002). The open source movement has relied upon controversial intellectual property rights that are rooted in the overall history of software development (Lerner & Tirole, 2002; von Hippel & von Krogh, 2003). By defining specific legal mechanisms and designing various software licenses, the open source phenomenon has successfully proposed an alternative software development model whose approach to the concept of intellectual property is quite different from that taken by traditional proprietary software. A separate article in this encyclopedia treats open source software communities in general as a type of virtual community. This article takes a historical approach to examining how the intellectual property rights that have protected free/open source software have contributed towards the formation and evolution of virtual communities whose central focus is software projects based on the open source model.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".