Bibliographic record
Abstract
This collection of works is part of the Canadian Legal Studies Series. The book takes a seven-part outlook on contemporary issues in electronic commerce in deftly organized way that captures subjects that are extremely interrelated. Part 1 is a general introduction to the complex nature of cyberspace, electronic commerce and information technologies, and the challenges they pose for social, legal, and economic regulation. Part 2 is a collection of materials discussing the dynamics of electronic commerce from diverse disciplinary perspectives. Parts 3 and 4 are respectively devoted to materials dealing with the sexy objects of regulation and jurisdiction in relation to cyberspace. Part 5 deals with domain names. Part 6 is titled “local functional issues”, and Part 7 concludes the work. This work draws from an impressive repository of diverse sources, making it a comprehensive work for mainstream researchers on a collection of fast evolving subject matters. The book draws very heavily on American law and legal issues and with moderate focus on Canadian jurisdiction in a manner that tempts one to think about a more exact title for the book than the present. This is an especially useful work for introducing researchers to the relevant issues in the field, and can help inspire meaningful and topical research projects.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.016 |
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".