An Assessment of the US Rules Which Determine the Relevant Law Applicable to Corporations: A Suggestion for Reform
Bibliographic record
Abstract
The article addresses one of the basic legal questions of corporations: which law governs disputes involving corporations? The US scholarship has not provided yet a comprehensive answer to this question. Which law, for example, applies to adjudicate a dispute between a Delaware corporation and a Nevada corporation, considering both usually conduct business in New York, California, Montana and Canada, with respect to delivery of goods in California? Through analyzing the external (i.e. aspects that relate to interactions between corporations and people/other corporations/bodies) and internal aspects of corporation (i.e. aspects related to the structure of corporate governance in terms of the relationship between corporate shareholders, directors, and officers), the article justifies some facets of current practices and makes key suggestions for reform. At a time when COVID-19 has caused economic disruption, corporations are inherently present in almost every aspect of our lives, and the volume of online commerce is escalating, the article tackles one of the most pressing and relevant questions of contemporary social reality.
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 | 0.044 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.012 | 0.047 |
| Scholarly communication | 0.029 | 0.033 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.026 | 0.031 |
| Insufficient payload (model declined to judge) | 0.006 | 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".