Perception, knowledge and attitudes of small animal practitioners regarding animal abuse and interpersonal violence in Brazil and Colombia
درک ، دانش و نگرش متخصصان حیوانات کوچک در مورد سوء استفاده از حیوانات و خشونت بین فردی در برزیل و کلمبیا-2019
Identification and report of animal abuse by veterinarians are fundamental to the promotion of animal welfare and the prosecution of this crime. Likewise, these professionals have an important responsibility to cope with the cycle of violence. This study aims to characterize the perception, knowledge, and attitudes of small animal practitioners regarding animal abuse and interpersonal violence in Brazil and Colombia. An online survey containing 27 questions was distributed to small animal practitioners of both countries. Multiple correspondence analysis (MCA) was employed to construct relationships among categorical variables and the chi-square statistic was used for testing these relationships. An important number of respondents had suspected that their patients could be victims of animal abuse (Brazil 48.1%; Colombia 64.5%). However, only a minority reported this situation to competent authorities (Brazil 32.7%; Colombia 10.8%). To receive training about veterinary forensics and/or animal welfare sciences in veterinary college was associated with identifying and denouncing animal abuse (p < .05). Deficiency in training received by veterinarians on veterinary forensic and animal welfare science in veterinary college was evident. Despite this, small animal practitioners recognize the existence of an association between animal abuse and interpersonal violence (Brazil 94.2%; Colombia 96.8%). The results highlight the need to strengthen education on animal abuse and promote the participation of veterinarians in the prosecution of this crime in Latin America.
Keywords: Veterinary education | Animal cruelty | Human-animal relationship | Companion animal maltreatment |Link theory
Gender differences among homicide offenders with schizophrenia in Hunan Province, China
تفاوت های جنسیتی در بین مجرمین قتل با اسکیزوفرنی در استان هونان ، چین-2019
This study aimed to understand the demographic, clinical and criminological characteristics of Chinese homicide offenders with schizophrenia from a gender-based perspective. Information on all homicide offenders with schizophrenia who received forensic psychiatric assessment between 2010 and 2016 in Hunan Province, China, was systematically retrieved (n=669). Gender differences in the above characteristics were analyzed, and independent correlates of homicide were explored. The male to female ratio of homicide offenders was about 4:1. Proportionally more males were single, unemployed and younger when committing their first crime than was apparent in females. Male perpetrators were more often influenced by delusions. Females were more likely to target their close family members. For males, living in rural areas and having a family history of mental disorder were positively associated with homicide, while having a criminal history and being unemployed were negatively associated. For females, younger age was positively, while being unmarried and unemployment were negatively associated with homicide. Our results indicate significant gender differences among Chinese homicide offenders with schizophrenia in demographic, clinical and criminological characteristics and in independent correlates of homicide. Further research in this field, especially aims at determining risk factors for crime in this population, should take the gender differences into account.
Keywords: Violence | Murder | Severe mental disorder | Sex difference | Independent correlates | Risk factors | Chinese
The reality behind the Istanbul convention: Shattering conservative delusions
واقعیت پشت پرده کنوانسیون استانبول: شکستن پندار محافظه کاری-2019
This paper analyzes the long process of ratification of the Istanbul Convention in Croatia and its political instrumentalization. The Convention was ratified in 2018, following a strong anti-ratification campaign which exemplifies the strengthening of a global pushback against womens rights. The conservative movement behind this campaign, which is still ongoing - with the shifted goal of withdrawing from the Convention through the mechanism of referendum, spread a number of misconceptions about the Convention, based foremost on the narrative that the Convention would impose an undesirable “gender ideology”. The aim of this paper is to shatter these delusions by first deconstructing the notions of gender, gender ideology and gender-based violence, and then by exploring the extent to which gender (identity) already plays a role within Croatian legal system, including through the jurisprudence of the ECtHR. The last part focuses on particular positive novelties the Istanbul Convention will bring to Croatian society.
Keywords: Sex | Gender | Gender-based violence | Istanbul convention | Gender ideology | Stereotypes
First do No harm: Medical legal violence and immigrant health in Coral County, USA
اول صدمه نبینید: خشونت حقوقی پزشکی و سلامت مهاجران در Coral County، USA-2019
Contemporary U.S. health and immigration policies exclude millions of noncitizens from healthcare coverage. Growing scholarship emphasizes legal status as a technology of social exclusion and determinant of health, but few studies capture the effects of recent policy uncertainty on noncitizen health. By examining the case of Coral County (a pseudonym), I highlight the challenges facing safety-net clinics and their noncitizen patients making life and death decisions amidst uncertainty before and after the 2016 presidential election. Observational and interview data with patients, clinic workers, and community partners (n=27) revealed that growing anxiety over federal immigration policies altered clinical risk calculations through a process I refer to as “medical legal violence” (MLV). Whereas previous risk negotiation strategies leveraged bureaucratic routines to elevate imminent threats of illness and/or injury in health decisions, heightened immigration enforcement under the Trump administration shifted the balance in clinical risk calculations toward social risks of detention, deportation, and family separation. This transformed clinical care in Coral County by turning trusted medical-legal bureaucracies into potential tools for federal biopolitical surveillance of immigrant patients, blocking healthcare pathways and increasing patients’ fear and anxiety.
Keywords: United States | Immigration status | Social determinants of health | Legal violence | Health inequalities | Medicaid | Safety-net clinics | Biopolitics
‘Maybe that’s how they learned in the past, but we don’t learn like this today’: Youth perspectives on violent discipline in Lebanon’s public schools
"شاید اینگونه است که آنها در گذشته یاد گرفتند ، اما ما امروز اینگونه یاد نمی گیریم": دیدگاه های جوانان درباره رشته های خشونت آمیز در مدارس دولتی لبنان-2019
This paper explores students’ experiences of violent school discipline in three urban public schools in Lebanon. Despite being banned by Lebanon’s Ministry of Education and Higher Education, violent discipline, including corporal punishment and verbal humiliation, emerged repeatedly from student accounts as a key barrier to school engagement. Drawing on ethnographic data and a conceptual framework informed by postcolonial and critical peace research, we consider the interaction of various forms of violence in students’ experiences of schooling and embed these within Lebanon’s larger sociohistoric, legal, and policy contexts. The findings point to linkages between poverty and violent discipline, suggesting a schema for understanding the intersection of violences in schools.
Keywords: Corporal punishment | Lebanon | Poverty | School discipline | Violence | Violent discipline
Why we should universalize the insanity defense and replace punishment with therapy and education
چرا باید دفاع جنون را جهانی کنیم و مجازات را با درمان و آموزش جایگزین کنیم؟-2019
The insanity defense, which exempts those judged to be insane from being punished for whatever illegal acts they have committed, exists in order to be the exception that proves the rule: namely, that illegal acts, except those committed by the insane, deserve punishment, since they are produced by a person who chose to do what he knew was wrong; and that the only questions we need to ask are moral and legal ones: “how evil was he, and how much punishment does he deserve?” This article will be devoted to showing why punishment, far from preventing violence, is the most powerful stimulant to violence that we have yet discovered; and that we need to replace it with empirically tested policies that do prevent violence. To speak of universalizing the insanity defense is simply another way to speak of abolishing punishment. The article will show why we should abandon the notion that prisons can be reformed, and instead replace them with safe, secure residential colleges and therapeutic communities. This would mean thinking of violence as a problem in public health and preventive medicine, about which we ask “what are the causes of violence, and how can we prevent it?”
Keywords: Violence | Punishment | Morality | Prisons | Insanity defense | Law
Violence against health professionals and facilities in China: Evidence from criminal litigation records
خشونت علیه متخصصان و امکانات بهداشتی و درمانی در چین: شواهدی از سوابق دادرسی کیفری-2019
Objectives: This study aims to extend the current understanding of violence against health professionals and facilities in China, with data from an authoritative, national-representative, but under-researched data source – litigation records, and discuss implications for developing violence prevention strategies. Design: We collected all legal cases relevant to violence against health professionals and facilities from criminal ligation records released by the Supreme Court of China from 2010 to 2016. Main outcome measures: (i) Characteristics of perpetrators: gender, age, education, occupation, history of mental illness and alcohol; (ii) characteristics of victims: medical specialization, location, type of violence; (iii) outcome of treatment. Results: 140 cases were collected for analysis. Beating, pushing, verbal abuse, threatening, burning mock paper money, placing a corpse in the hospital, hanging banners, blocking hospital gates and doors, and smashing hospital property were the most frequently reported types of violence. Specifically following patient deaths, the interval between a patients death and violence by the patients families and friends was short, with 51% happening on the same day. Conclusions: Our study provides a comprehensive overview of violence against health professionals and facilities in China, which can be used to inform the development of prevention strategies.
Keywords: Violence against health professionals | Criminal litigation records | Health system reform | Health policy
Clustering suicides: A data-driven, exploratory machine learning approach
خودکشی های خوشه ای: یک رویکرد یادگیری ماشین اکتشافی مبتنی بر داده ها-2019
Methods of suicide have received considerable attention in suicide research. The common approach to differentiate methods of suicide is the classification into “violent” versus “non-violent” method. Interestingly, since the proposition of this dichotomous differentiation, no further efforts have been made to question the validity of such a classification of suicides. This study aimed to challenge the traditional separation into “violent” and “non-violent” suicides by generating a cluster analysis with a data-driven, machine learning approach. In a retrospective analysis, data on all officially confirmed suicides (N = 77,894) in Austria between 1970 and 2016 were assessed. Based on a defined distance metric between distributions of suicides over age group and month of the year, a standard hierarchical clustering method was performed with the five most frequent suicide methods. In cluster analysis, poisoning emerged as distinct from all other methods – both in the entire sample as well as in the male subsample. Violent suicides could be further divided into sub-clusters: hanging, shooting, and drowning on the one hand and jumping on the other hand. In the female sample, two different clusters were revealed – hanging and drowning on the one hand and jumping, poisoning, and shooting on the other. Our datadriven results in this large epidemiological study confirmed the traditional dichotomization of suicide methods into “violent” and “non-violent” methods, but on closer inspection “violent methods” can be further divided into sub-clusters and a different cluster pattern could be identified for women, requiring further research to support these refined suicide phenotypes.
Keywords: Suicide | Suicide methods | Machine-learning | Violent suicide | Cluster analysis
Navigating Big Data dilemmas: Feminist holistic reflexivity in social media research
مرور معضلات داده های بزرگ: بازاندیشی جامع فمینیستی در تحقیقات رسانه های اجتماعی-2018
Social media offers an attractive site for Big Data research. Access to big social media data, however, is controlled by companies that privilege corporate, governmental, and private research firms. Additionally, Institutional Review Boards’ regulative practices and slow adaptation to emerging ethical dilemmas in online contexts creates challenges for Big Data researchers. We examine these challenges in the context of a feminist qualitative Big Data analysis of the hashtag event #WhyIStayed. We argue power, context, and subjugated knowledges must each be central considerations in conducting Big Data social media research. In doing so, this paper offers a feminist practice of holistic reflexivity in order to help social media researchers navigate and negotiate this terrain.
Keywords: Feminist ethics | feminist holistic reflexivity | feminist methodologies | domestic violence | social media | Big Data
شناسایی زبان خشونت آمیز (پرخاشگرانه) با استفاده از ویژگی های جداساز (تعبیه شده) و احساسی
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 15
این مقاله مشارکت ما را در اولین تکلیف مشترک در شناسایی پرخاشگری توصیف میکند. روش پیشنهادی متکی بر یادگیری ماشین برای شناسایی متن های رسانهای اجتماعی است که دارای پرخاشگری هستند. ویژگی های اصلی مورد استفاده در روش ما اطلاعات استخراج شده از کلمه جداساز و خروجی آنالیز احساسی میباشد. چندین روش یادگیری ماشین و ترکیبهای مختلف ویژگی ها امتحان شدند. ملاحظات رسمی از ماشینهای بردار پشتیبان و جنگلهای تصادفی استفاده کرد. ارزیابی رسمی نشان داد که برای متون مشابه آنهایی که در مجموعه داده آموزشی هستند، جنگلها به بهترین نحو کار میکنند، در حالی که برای متونی که svmها متفاوت هستند انتخاب بهتری هستند. این ارزیابی همچنین نشان داد که با وجود سادگی روش، این روش در مقایسه با روش های دقیقتر عملکرد خوبی دارد.
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