Contract Cheating and Ghostwriting among University Students in Health Specialties
Bibliographic record
Abstract
Contract cheating and ghostwriting are forms of misconduct that are unethical and a serious academic issue, especially among healthcare professionals, as they directly impact patient health. To date, research on this area in the Middle East has been limited. Therefore, we used a validated self-administered questionnaire to investigate the awareness, perceptions, and reasons for these behaviors among 682 students in health specialties at five universities in Riyadh, Saudi Arabia. The majority of the students (60.1%) were unaware of the terms "contract cheating" and "ghostwriting," and 69.5% had not received any prior training on integrity. However, having prior training had a positive effect on awareness levels, and respondents attending private universities were significantly more aware than those attending public universities. The factors that contributed to contract cheating behavior included poor time management, English language difficulties, and a lack of writing skills. These findings emphasize the need for integrity training at the national level to raise awareness.
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How this classification was reachedexpand
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 | 0.204 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.039 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".