The impact of Supreme Court employment law cases : leading lawyers analyze recent decisions and their impact on employment law
Bibliographic record
Abstract
The Impact of Supreme Court Employment Law Cases provides an authoritative, insiders perspective on influential Supreme Court cases from 2010 and their impact on employment law. Featuring partners from some of the nations leading law firms, these experts analyze developments in the area of employment law through the lens of Supreme Court cases like Conkright v. Frommert, Lewis v. City of Chicago, City of Ontario v. Quon, and New Process Steel v. National Labor Relations Board. These top attorneys discuss the responses of lawyers and their clients to recent changes and introduce new procedures and practices that have been implemented to help better serve clients. These authors also offer their predictions on what lies ahead for employment law in the upcoming year by previewing cases that are set to be decided by the Supreme Court. The different niches represented and the breadth of perspectives presented enable readers to get inside some of the great legal minds of today, as these experienced lawyers offer up their thoughts around the keys to success within this ever-evolving area of law.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".