The Virtual World as a Company Town - Freedom of Speech in Massively Multiple Online Role Playing Games
Bibliographic record
Abstract
In the 21st century, traditional company towns like Chickasaw, Alabama, where a corporation steps into the shoes of the state for purposes of the First Amendment, are almost non-existent. This paper postulates that they have been replaced by Massively Multiple Online Role Playing Games (MMORPG's) such as EverQuest, The Sims Online and Second Life where many individuals have extensive social circles, own property, and even hold down virtual jobs. According to surveys, some of these individuals actually spend more time each week in the virtual world than pursuing basic real world activities such as working, eating and sleeping. In 2004, one of these virtual worlds, There, entered into a contract with the US Army to create a full-scale, 1:1, virtual replica of the entire earth for purposes of combat simulations, known as the Asymmetric Warfare Environment (AWE). The paper hypothesizes a post-war scenario whereby this immense platform is transferred to private corporations in the same manner that the ARPANET, the military ancestor of the Internet, was devolved into private hands. This universal virtual world may become the successor to the Internet as we know it today and will become a place where the majority of us choose to shop, socialize and do business. The paper emphasizes that the case law on freedom of speech in MMORPG's will have a profound precedent setting effect on how the First Amendment is applied to this coming universal virtual platform, since the legal principles concerning new technologies tend to be set at an early stage of their development. If the right road is not taken, then we run the risk that the coming universal virtual world will be, from a freedom of speech perspective, a nightmarish endless global shopping mall, instead of an empowering enhancement of the real world with its boundless opportunities for encounters with those of differing viewpoints.
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.
How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".