The Global Employer: Equity in the Workplace
Bibliographic record
Abstract
[Excerpt] This issue contains a collection of articles from 13 jurisdictions which examine various issues regarding equality in the workplace. Countries continue to pass new legislation that aims to create an equal environment for all employees regardless of age, gender, or race. One issue that continues to be at the forefront is the right to equal pay for equal work which is addressed in articles from Argentina, Austria, Canada, Colombia, Japan, and Russia where the principle of equal pay for equal work, regardless of gender, race, nationality, religious beliefs, etc., is examined. The issue of pay equity is further examined in articles from Germany and Mexico where the equal pay principle is extended to agency workers and when dealing with outsourcing companies; and in Vietnam where there is discussion of new legislation to harmonize the minimum wage. Articles on benefits are also included, such as the new termination law in Belgium which eliminates the difference in notice requirements for blue and white collarworkers and the new vacation legislation in The Netherlands which ensures equal accrual of vacation time for all employees. Other articles include one from the United Kingdom where gender equality in the boardroom is examined and articles from the United States where diversity in the workplace and California's Transparency in Supply Chains Act of 2010 are discussed in depth.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.011 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 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".