Bibliographic record
Abstract
Companion website: http://www.nyupress.org/fap Yesterday's battles over internet turf were fought on the net itself: today's battles are fought in government committees, in Congress, on the stock exchange, and in the marketplace. What was once an experimental ground for electronic commerce is now the hottest part of our economic infrastructure. In From Anarchy to Power, Wendy Grossman explores the new dispensation on the net and tackles the questions that trouble every online user: How vulnerable are the internet and world wide web to malicious cyber hackers? What are the limits of privacy online? How real is internet addiction and to what extent is the news media responsible for this phenomenon? Are women and minorities at a disadvantage in cyberspace? How is the increasing power of big business changing internet culture? We learn about the political economy of the internet including issues of copyright law, corporate control and cryptography legislation. Throughout the book the emphasis is on the international dimensions of the net, focusing on privacy and censorship in the United States, Europe and Canada and the hitherto ignored contributions of other countries in the development of the net. Entertaining and informative From Anarchy to Power is required reading for anyone who wants to know where the new digital economy is heading
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".