Sexual harassment in academia - perception understanding and reporting of sexual harassment in a Southern African University.
Bibliographic record
Abstract
The study was conducted to explore the perspectives understanding and reporting patterns of sexual harassment among staff and students at the University of Zambia (UNZA). The participants included 76 academic staff 128 non academic staff and 885 students who were randomly selected from the different schools at UNZA. A self-reported questionnaire was developed and piloted for use in this study. The results indicated that sexual harassment occurred among different categories of the UNZA community with 37% of all the participants reporting to have been sexually harassed. There was found to be a discrepancy in the understanding of the term sexual harassment with majority of the participants only recognizing overt acts such as “subtle or overt pressure for sexual favors” to be acts of sexual harassment. Reporting of sexual harassment was found to be minimal with only a quarter of those who were sexually harassed having told someone about the act. The majority of those who were sexually harassed did not make a formal complaint because they were embarrassed or they did not believe any action would be taken. It may be concluded that sexual harassment at the UNZA is a challenge to be addressed seriously.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".