Prevalence of Sexual Assault in Abakaliki, Ebonyi State, Nigeria
Bibliographic record
Abstract
BACKGROUND: Sexual assault (SA) is an umbrella terminology which encompasses a wide range of sexual offenses extending to actual or attempted unlawful sexual penetration also called rape. It is a common phenomenon which occurs worldwide. OBJECTIVES: To estimate the prevalence of different types of sexual assault and to describe the methods of penetration used (e.g., incapacitation, physical force, verbal coercion). METHOD: This study was carried out at the Department of Morbid Anatomy, Federal Teaching Hospital, Abakaliki and it was a one year retrospective study in which cases of rape were reviewed. The work analyzed 31 cases of rape in Accident and Emergency Department of the Hospital over a one year period from January 2017 to December 2017. RESULT: The mean age (in years)of all subjects in this study was 32.09±17.9 SD. The age range was 0–59 years. The groups of highest number of cases (12, 38.7%; 11, 35.5%) were at the age groups 10-19 years and 0-9 years, respectively. In addition, there was no case of rape involving any male victim in this study. Moreover, no case involving females aged 60 years and above was seen. Children were found to be sexually abused more than the adults. The differences between age distributions of cases according to sex in this study were statistically significant with the P-value of 0.001. Neighbors were discovered to be the highest perpetrators of sexual assault accounting for the highest number of cases 8 (25.8%). In most cases 20 (64.5%), the victims were raped by single assailant and the majority of them in this category were children. CONCLUSION: Although the prevalence of sexual assault in this study appears to be low, it confirms the existence of the phenomenon in Abakaliki, Nigeria, and a major cause for concern is the fact that those affected were predominantly young children. To curb this heinous act, parents must be vigilant and closely monitor their children, while the government should enact stringent laws and be ready to wield the big stick in situations of need.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".