Why the solutions put in place to combat moral harassment in the world of work so far failed to eradicate the phenomenon? Comparative analysis between France and Canada.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This thesis will focus on psychological harassment in the workplace. As we are studying management and international issues, we will analyse moral harassment in France and Canada. In the first part, we will analyse psychological harassment in its global form. We will study its sources, its forms and its sustainability. \nWe will also analyse the consequences this has on victims, companies and relatives. Then we will study the actions put in place to fight against moral harassment. In the course of this paper, we will see that moral harassment remains a taboo subject in companies, which allows the phenomenon to continue. \nThis research highlighted the need to continue to measure the phenomenon and evaluate the control actions put in place to keep only those that could prove effective. The studies, surveys and memoirs that we hope to see in the future will be, each at its own level, useful in order not to forget this scourge.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it