Domestic Violence Rates in NSW

Document Type:Research Paper

Subject Area:English

Document 1

Although several researches have been conducted, that have concentrated on the statistics on the domestic violence. Others have dealt with types of crimes in the local governments. A research done in September 2018 by the department of Justice (AU) indicated that sexual assault had gone up by 3. while indecent assault, act of indecency and other sexual offences had rose by 3. These are some of the domestic violence in NSW (AU) local government area. It shows that the condition is getting worse. None of the conducted studies have tried to establish factors that accelerate the domestic violence. If the factors that increase the domestic violence are identified, then it would be easier for the authorities to eradicate the menace. This study hence aims to establish the factors that influence domestic violence in NSW (AU) local government area. These factors are going to be identified through correlation analysis. A model will then be built to predict domestic violence. The model will be based on crime dataset provided by the NSW local government area. The dataset contains 7942 attributes. Therefore the methodology applied is feature selection, which indicates the hypothesis that potential risk as the factors such as age, relationships status, and culture, respondent’s income and also the respondent’s level of education. Literature and Theory Toby D. Goldmin in his research paper “What Causes Domestic Violence” defines domestic violence as when one partner in an intimate relationship abuses the other. The form of abuse can either be physical, sexual emotional or combination of all.

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The study found out that women are the common victims of domestic violence. Another study in (Social Problems, 34,187) reported that 92 percent of women who had experience domestic violence did not reveal it to their physician while 52 percent had not discussed that they are going through domestic violence with anyone. Another bitter fact is that the National Crime Survey found that 48 percent of aggregate domestic violence went unreported to the law enforcements. As a result of all these domestic violence issues, the study established that children who witness the violence are greatly affected and have problems schooling and also socialization. World Health organization conducted a study in Zimbabwe regarding domestic violence in the year 2016 and the results were shocking. The study found that there was a significant connection between domestic violence and HIV/AIDs.

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This is because males who were violent did not negotiate on safer sex with their wives and most remained unfaithful. Another study in the same country found out that 26 percent of women aged 18 and over were being forced into sex that they did not want. The data contains 7942 attributes and two label cases. The first dataset contains cases of domestic violence in various local government areas from the year 1999 to 2018. We will use this data to show aggregate domestic violence within different areas and also show the trend of domestic violence with respect to year. We will also be able to identify the local government areas with the highest recorded number of domestic violence in given years. The data set will also help us identify whether there is significant difference in average number of domestic violence cases within the local government areas.

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nc nc Assault Domestic violence related assault 29,209 388. Stable Stable Sexual offences Sexual assault 933 12. Stable Up 5.   Indecent assault, act of indecency and other sexual offences 636 8. Stable Up 6. The model was evaluated by test dataset. There were two classes of dataset, A and C which is binary classification problem. Since the dataset is binary, the appropriate model is the logistic model. The model and other classification models were used in this project. Using the Logistic regression, we get an accuracy of 0. se indicates the standard error. From the table above, females aged between ages 20 and 24 had 0. unit fewer domestic cases than their counterpart. We also establish that males between 45 and 54 years had 0. more unit of domestic violence cases as compared to the rest of the men. This was because the dataset had a very large number of variables.

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The final step was to model the selected variables. The model was evaluated by test dataset. There were two classes A and C, which had binary classification problem hence the most appropriate model was the logistic regression. Other classification models were used in this project. Mehr Khan, 2000. Director, UNICEF Innocenti Research Centre: DOMESTIC VIOLENCE AGAINST WOMEN AND GIRLS. Rik Sutherland, St Vincent de Paul. Causes of Domestic Violence, and Implications for Primary Prevention. Sílvia Fraga. Partnerships with the Media to Prevent Domestic Violence, in ‘Too Close to Home: Domestic Violence in the Americas’ op. cit. United Nations (1993) Strategies for Confronting Domestic Violence: A Resource Manual. New York: United Nations. Edelson J.

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