Legal and Ethical Implications of Verbal Abuse in the Workplace: Upholding Dignity and Respect for All
Bibliographic record
Abstract
This research paper examines the legal and ethical ramifications of shouting at a colleague or any individual, including marginalized groups, in a workplace setting. It explores various legal frameworks, including anti-bullying, harassment, and occupational safety laws across jurisdictions like the United States, Canada, Europe, Australia, the Czech Republic, and India, with a focus on the Indian Penal Code and the Sexual Harassment of Women at Workplace Act, 2013. The paper highlights the moral right to live with dignity, emphasizing that no one has the right to shout at another person, whether a colleague or a ragpicker, and that individuals, such as ragpickers, have the right to assert, "I am doing my job; what is your right to shout at me?" Jurisdictional differences, workplace policies, and the psychological and social impacts of verbal abuse are analyzed, alongside the victim's right to a safe and respectful environment. The study underscores the need for robust legal protections, effective organizational policies, and cultural shifts to prevent verbal abuse and promote workplace dignity.
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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.061 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".