Bibliographic record
Abstract
Freedom, liberty, and autonomy are the ideals mainly associated with Internet's first generation of thinkers, writers and "netizens," those who helped forge the Internet and the early technological and intellectual foundations of the idea of “cyberspace.” These ideas were, says Lawrence Lessig, the “founding values of the Net” and inspired an entire generation of scholarship focused on preserving the free and open nature of the Internet’s culture and architecture. But what has anyone to say about equality? Few, if any, Internet scholars today focus on equality as a similar value to be promoted or achieved. Returning to some of the early influential Internet texts, this Article argues that equality was also heralded as another important value that the Internet could promote, but has since been largely neglected, including the ways that the Internet can actually promote or entrench inequality. It then offers reasons for this neglect -- such as the predominance and influence of libertarian oriented "cyber-utopian" works -- and provides an account of the different challenges for equality and distributive justice in relation to the Internet, including inequalities of ICT access, connectivity, security, and experience in online communities. It concludes with a discussion of measures to help address these digital divides.
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 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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".