Police Record Research Articles

REVIEW OF LEGAL PROFESSIONAL ETHICS TOWARDS INVESTIGATORS IN THE CRIMINAL CASE OF FOUR STUDENTS REFUSING OMNIBUS LAW

The way investigators handled students who were involved in the demonstration to ratify the Job Creation Act did not reflect the slogan of protecting, nurturing, and serving the community carried by the institution. Instead of fostering and protecting the future of students, the police criminalize them. The police arrested students and students who opposed the job creation law in a number of areas last week. The police accused them of being anarchist. The police also threatened to include the status of law violators so that they would not issue a police record certificate (SKCK). Student involvement in demonstrations is not a criminal act. Moreover, students' and students' criticism of the Job Creation Act is actually a reaction to the inherent defects of the omnibus law. Not only is its preparation not transparent, the substance of the universal sweeping law also harms workers and threatens the environment. The case of students who are victims of criminalization for refusing the Omnibus Law is still continuing its legal process to this day. However, the trial which is supposed to be the place to seek justice is run very subjectively and full of flaws. This further confirms that no violation of Professional Ethics conducted by investigators to the students repellent Omnibus.

Guilty Until Proven Guilty

The journey to understand technological and digital policing requires a re-engagement with the most basic and widely used technology – paper-based registers for preventive policing. In the name of preventive policing, people from ex-untouchable castes, indigenous populations, and immigrants (in the city) are put under surveillance and recorded in registers. In the process, they earn criminal records for petty crimes, but also for no crimes at all. The registers enable a very ‘visible’ surveillance, where the ‘suspects’ are watched, followed and asked to come for mandatory attendance at the stations. Keeping in mind the segregated nature of the urban landscapes of cities in India, this is only possible for people who belong to certain strata of society and who do not have the privilege of escaping the prying eyes of the police. Researchers have argued that this form of policing is anti-poor or anti-marginalised. However, in this article, I argue that this form of preventive policing is better understood as being anti-caste. I demonstrate how police manuals, including guidelines for police record keeping and surveillance practices, reproduce and imitate the caste based social structure of India by using legacy practices from some still operational and some defunct laws. The paper-based registers maintain an illusion of objectivity – while the police can simply claim to be obeying the manuals. However, by enabling the recording of only those able to be visibly surveilled, those arrested for petty crimes, or those unable to escape the criminal justice system because of lack of money or social support or both, the paper-based registers become a vehicle of policing caste. By marking those thus recorded as habitual offenders, these registers propagate the caste-based understanding that defines crime as an inherent/hereditary trait of the lower castes. Prediction becomes nothing more than a self-fulfilling prophecy.

The Ontario Domestic Assault Risk Assessment: Predicting Violence Among Men With a Police Record of Intimate Partner Violence in the United States

The Ontario Domestic Assault Risk Assessment (ODARA) is an actuarial risk assessment tool for intimate partner violence (IPV) recidivism. Despite its international use, there is no published validation of the ODARA’s predictive accuracy in a U.S. sample. We studied 356 men in New York police records of IPV against a female partner to examine the ODARA’s predictive accuracy for IPV recidivism (base rate 35%), non-IPV violent recidivism (against a nonpartner; 16%), any violent recidivism (49%), and nonviolent recidivism (50%), in a fixed 2-year follow-up. Using 11 scorable ODARA items, area under the curve values were significant and ranged from .590 to .630, indicating small to medium effects. Expected/Observed indices revealed poor calibration with 2-year IPV recidivism rates in ODARA construction and cross-validation samples. Findings support the generalization of the ODARA’s predictive accuracy in different populations and outcomes, but a need for new norm development for higher risk populations.

Policing and Mental ill-health: Using Big Data to Assess the Scale and Severity of, and the Frontline Resources Committed to, mental ill-health-related calls-for-service

Abstract Addressing public safety and welfare, inclusive of responding to incidents involving persons with mental ill-health (PMIH) has become an integral dimension of, and a significant challenge to, contemporary policing. Yet, little is known of the scale and severity of such PMIH-related policing demand, nor of the extent of frontline resource consumed in resolving such incidents. To address this shortfall, we deploy a bespoke text mining algorithm on police incident logs to estimate the proportion and severity of calls-for-service involving PMIH in a study of Greater Manchester, UK. Furthermore, and using Global Positioning System data, we then assess the amount of time spent by frontline officers responding to these calls. Findings suggest that existing police recording practices serve to significantly underestimate the scale and severity of PMIH-related demand. The amount of time spent dealing with PMIH-related incidents is both substantial and disproportionate relative to other forms of police demand.

Deaths and Injuries from Unintentional Falls: An Analysis of Nepal Police Records

Falls are a major cause of unintentional injury-related global mortality and morbidity. The actual mortality and morbidity from falls in Nepal have been overlooked and not systematically studied. This study, therefore, aims to present the national status of fall-related deaths and injuries. The study analyzed the fall incidents recorded by Nepal Police for five fiscal years (17 July 2014 to 16 July 2019). These incident recordings were in the form of narratives, and possible variables were extracted for the analysis. In five years, 4,714 people were injured or died from falls in Nepal. The average age of the fall victim was 35.6 years (SD=19.94); the mean age of the person who died from falls was slightly lower (30.9 years) than the injured person (40.4 years). The analysis showed that the fall cases were remarkably greater for males than females. This study found that Bagmati Province, where the capital city was located has the highest death and injury rates from falls, followed by Gandaki Province and Province 1. The study identified 11 different locations of falls. These findings revealed that Nepal has a considerable burden of fall deaths and injuries. However, the actual burden of fall injuries might be higher due to the under-reporting of the incidents through the Nepal Police data recording system.

Tracking Violent Crime with Ambulance Data: How Much Crime Goes Uncounted?

Research QuestionWhat proportion of ambulance records documenting injuries caused by criminal violence is included in police records for violent crimes occurring in the same area at the same dates and times as incidents found in ambulance records?DataWe analysed subsets of three datasets during matched time periods: West Midlands Ambulance Service records of all 36,639 incidents of violent injuries from January 2012 to March 2017; 132,317 West Midlands Police records of violent crimes from January 2012 to December 2015; and 9083 records of treatment of violent injuries as recorded in hospital Emergency Department (ED) records covering September 2013 to March 2016.MethodsWe compared all incidents in the ambulance dataset and ED data to corresponding locations and times in incidents recorded in police datasets.FindingsApproximately 90% of cases in the ambulance dataset did not have a corresponding case in the police dataset. The proportion was even lower in the Emergency Department dataset, where less than 5% of cases were successfully matched to a police record. These data suggest that adding the medical data to the police data could add 15 to 20% more violent offences to the totals recorded by the police.ConclusionsTracking identified ambulance data can add substantial numbers of serious violent crimes, over and above those reported to the police. These added cases can increase the targeting of police and public health resources to prevent harm against victims, at places, and by offenders at highest risk of serious violence.

Categories for Non-Compliance of Movement Control Order in Malaysia: A Review through Online News Report

The Movement Control Order (MCO) has been enforced on 18th March 2020 following the COVID-19 pandemic in Malaysia. This MCO is hoped that it is able to lower the number of infection cases in Malaysia. However, some groups of societal members were found as non-compliant with the MCO as reported by the online news. The objective of this research was to identify the display category on the news of non-compliant citizens in MCO period. Data analysis had been performed on online news starting from 18th March 2020 until 28th April 2020 which is based on MCO Phase 1 up to Phase 3. More than 100 online news headlines about MCO violation had been analysed using content analysis method based on Social Interaction Theory. The research outcome has found that social interaction plays a vital role in non-compliance issue within the enforcement period of MCO as reported by online news. The categories for non-compliance of MCO are as follows i) Movement without a valid reason, ii) Sports and recreational activities, iii) Religious activities, iv) Visiting and having feast, v) Chatting at restricted area, vi) Drugs-related violation, vii) Crime involvement and police record, viii) Gambling and Entertainment, ix) Intake of drinks leading to intoxication and imagination and x) Violation by foreigners. The use of social interaction theory in this research has clearly illustrated that non-compliance of MCO shows self-control of the perpetrator as a result of social control is very weak. Generally, the violation of MCO has a relationship with the environment of social interaction. Social interaction has a conflict that leads to deviant act which causes the breach of rules and norms.

Psychological autopsy study comparing suicide decedents with and without a history of suicide attempts in a nationwide sample of South Korea.

The majority of suicide decedents die on their initial attempt. To bring attention to suicide decedents without a suicide attempt history, the current study explored their demographic, clinical, and suicide-related characteristics. The data were derived from the Korea National Investigation of Suicide Victims Study, which assessed all suicide cases from 2013 to 2017 recorded in police investigation reports. We compared suicide decedents with and without a history of nonfatal attempts using the Korea Psychological Autopsy Checklist for Police Records (K-PAC). Out of 5228 cases included in our study, 3147 (60.2%) died on their first suicide attempt. Demographically, those who were male, older than 65, employed, and married/widowed were more likely to die on their initial attempt. Clinically, those who died on their initial attempt were more likely to have never been diagnosed with psychiatric disorders, whereas those who died on a repeated attempt were more likely to have been diagnosed with mood disorders. In terms of suicide-related factors, experiencing relationship problems and complaining about physical discomfort were associated with dying on an initial attempt. Depressed affect, self-harming behaviors, and talking about suicide or death were associated with repeated attempts.

An autopsy study of 328 cases of fatal motor cycle accidents

Background: In India Fatalities due to Motor Cylce Accidents is not uncommon and remained a major reason of Public Health Issue despite Government Measures. Aim: 1) To study the Pattern,Nature & Distribution of Injuries. 2) To Identify the Fatal Injuries. 3) The Age & Sex Distribution of the Victims. 4) To study the Impact of Helmet Law on preventing Head Injuries. Methodology: This Prospective Study was an Autopsy based Study done during the period 2013 to November 2020 in Bangalore, India. A Total of 328 cases were Studied during this period. The data obtained during Autopsy was Registered in Autopsy Reports and The Autopsy report Data was recorded in a Register and Then analyzed on Yearly Basis. Information also retrieved from Police Records. Only the Motorcycle Rider Fatalities are Studied. The Pillion rider Fatalities are Excluded in the present study. Results: A total of 2368 Autopsy conducted during the period of Study, of which 1169 were Death due to Road Traffic Accidents. Fatal motor Cycle Accidents Accounted for 328 cases,14% of Total Autopsies. Males Contributed to 84% of the Fatalities. Major number of Cases were reported from the age group 21-30years. Head Injuries accounted for 87%[n-285] of Injuries and were the major Fatal injury reported. Crush Injury to The Chest was least Reported. Majority of the Abdominal Injury resulted in Liver Lacerations in 42% of the Cases. Majority of the Injuries to the Extremities reported were Fractures involving the Upper Limbs in 39%[n-128] of the cases. Maximum Fatalities were reported from Motorcyclist without wearing the Helmet in 87.5% [n-287] of the cases despite the Legislation by the government. Conclusion: Head Injuries were the Major Cause of Fatality. Maximum Number of Fatalities reported due to Failure to Wearing Helmets. Males were Five times More Affected than Females. Major Fatalities reported between 21-30years.

Comparing warning signs of suicide between suicide decedents with depression and those non-diagnosed psychiatric disorders.

Early recognition of a high-risk group impending suicide is important. We aimed to compare warning signs depending on the nature of the psychiatric disorder and whether it was a documented diagnosis. Data of suicide decedents were collected from police records from 2013 to 2017. We evaluate psychiatric symptoms and warning signs in three aspects (language, behavior, and affect) using the Korea-Psychological Autopsy Checklist for Police Records (K-PAC-PR). A total of 13,265 suicide decedents were recruited for this study. Of them, 66.9% of females and 46.7% of males diagnosed psychiatric disorders, with depressive disorder being the most common one. Warning signs were observed in 93.0% of suicide decedents. They were observed more in those who were diagnosed with psychiatric disorders, especially in those with a depressive disorder. "Talking about dying or suicide" was the most common warning sign in all groups, and "apathetic behavior" was the most related warning sign for depressive disorder. Especially for "talking about dying or suicide," the proportion of observed "within a week" was high, making it valuable as a warning sign. Warning signs were commonly found in suicide decedents regardless of gender. They were more common among the decedents diagnosed with psychiatric disorders, especially among those with a depressive disorder.

Utilizing Text Mining, Data Linkage and Deep Learning in Police and Health Records to Predict Future Offenses in Family and Domestic Violence.

Family and Domestic violence (FDV) is a global problem with significant social, economic, and health consequences for victims including increased health care costs, mental trauma, and social stigmatization. In Australia, the estimated annual cost of FDV is $22 billion, with one woman being murdered by a current or former partner every week. Despite this, tools that can predict future FDV based on the features of the person of interest (POI) and victim are lacking. The New South Wales Police Force attends thousands of FDV events each year and records details as fixed fields (e.g., demographic information for individuals involved in the event) and as text narratives which describe abuse types, victim injuries, threats, including the mental health status for POIs and victims. This information within the narratives is mostly untapped for research and reporting purposes. After applying a text mining methodology to extract information from 492,393 FDV event narratives (abuse types, victim injuries, mental illness mentions), we linked these characteristics with the respective fixed fields and with actual mental health diagnoses obtained from the NSW Ministry of Health for the same cohort to form a comprehensive FDV dataset. These data were input into five deep learning models (MLP, LSTM, Bi-LSTM, Bi-GRU, BERT) to predict three FDV offense types (“hands-on,” “hands-off,” “Apprehended Domestic Violence Order (ADVO) breach”). The transformer model with BERT embeddings returned the best performance (69.00% accuracy; 66.76% ROC) for “ADVO breach” in a multilabel classification setup while the binary classification setup generated similar results. “Hands-off” offenses proved the hardest offense type to predict (60.72% accuracy; 57.86% ROC using BERT) but showed potential to improve with fine-tuning of binary classification setups. “Hands-on” offenses benefitted least from the contextual information gained through BERT embeddings in which MLP with categorical embeddings outperformed it in three out of four metrics (65.95% accuracy; 78.03% F1-score; 70.00% precision). The encouraging results indicate that future FDV offenses can be predicted using deep learning on a large corpus of police and health data. Incorporating additional data sources will likely increase the performance which can assist those working on FDV and law enforcement to improve outcomes and better manage FDV events.

Factors affecting the establishment of the size and limits of an administrative area supervised by a local police officer

The research subject is social relations in the field of public order protection, ensuring social security and combating crime in an administrative area and the implementation of preventive measures by a local police officer. The authors focus on the factors and peculiarities of the supervised area and its population affecting the establishment and revisioning of the size and limits of an administrative area supervised by a local police officer, and on the amendments to the decree of the Ministry of Internal Affairs of March 29, 2019 No205 “On a local police officer service in an administrative area and organization of this service”. Based on the conducted analysis, the authors suggest, when defining the size and limits of an administrative area, taking into account the population density in the area in question, economic, geographic, national and demographic peculiarities on the territory, the criminological characteristics of the citizens, the number of citizens having a police record, the current operative situation, and the peculiarities of administrative organization of municipal entities. In the authors’ opinion, the resolution of this problem will have a positive effect on the work of police officers, and will help to equally and rationally distribute workload on local police officers thus raising the effectiveness of their service and improving the quality of preventive measures.   

Completeness of Police Records for Injury Surveillance: A Systematic Review

Completeness of Police Records for Injury Surveillance: A Systematic Review

Prevalence of Mental Illnesses in Domestic Violence Police Records: Text Mining Study

BackgroundThe New South Wales Police Force (NSWPF) records details of significant numbers of domestic violence (DV) events they attend each year as both structured quantitative data and unstructured free text. Accessing information contained in the free text such as the victim’s and persons of interest (POI's) mental health status could be useful in the better management of DV events attended by the police and thus improve health, justice, and social outcomes.ObjectiveThe aim of this study is to present the prevalence of extracted mental illness mentions for POIs and victims in police-recorded DV events.MethodsWe applied a knowledge-driven text mining method to recognize mental illness mentions for victims and POIs from police-recorded DV events.ResultsIn 416,441 police-recorded DV events with single POIs and single victims, we identified 64,587 events (15.51%) with at least one mental illness mention versus 4295 (1.03%) recorded in the structured fixed fields. Two-thirds (67,582/85,880, 78.69%) of mental illnesses were associated with POIs versus 21.30% (18,298/85,880) with victims; depression was the most common condition in both victims (2822/12,589, 22.42%) and POIs (7496/39,269, 19.01%). Mental illnesses were most common among POIs aged 0-14 years (623/1612, 38.65%) and in victims aged over 65 years (1227/22,873, 5.36%).ConclusionsA wealth of mental illness information exists within police-recorded DV events that can be extracted using text mining. The results showed mood-related illnesses were the most common in both victims and POIs. Further investigation is required to determine the reliability of the mental illness mentions against sources of diagnostic information.

Weighting Terms and Procedures Against Citizens In Regaining Indonesian Citizenship

<em>The reciprocal relationship between the state and citizens is seen in the granting of citizenship status and obedience to the law by citizens. Citizenship status is important in determining this relationship. The problem in this study is what are the implications of the release of citizenship status in Indonesia and what are the ideal terms and procedures for regaining Indonesian citizenship This research is a normative study using a statutory approach, case approach and conceptual approach. The loss of citizenship status has implications for not fulfilling one's basic rights that can be granted by the state. Therefore, it should be subject to weighting conditions and procedures by adding provisional length of stay of 10-15 years, add 'lost citizenship' note to the police record and to the residence permit, increase Citizenship money, do social work for a certain time, announce the action in media, and temporarily suspend the application for citizenship</em>

Tecnologías de identificación y clasificación social: el Fondo de Prontuarios Policiales del Chubut

Este artículo describe el Fondo de Prontuarios Policiales del Chubut (FPPC), contextualizando la producción de los documentos que lo componen, y caracterizando las tecnologías de identificación que se emplearon para clasificar la población y controlarla conforme a la legislación nacional y los tratados internacionales suscritos por la Argentina. Se destaca el valor del Fondo, considerando que los prontuarios ofrecen información de síntesis sobre miles de habitantes del Chubut con fechas extremas de documentación desde fines del siglo XIX. Finalmente, se argumenta que este repositorio presenta potencialidades para diferentes líneas de investigación, considerando la diversidad tipológica y sus magnitudes.

Out from the Curtains of Secrecy: Private University Police and State Open Records Laws

The role of police officers on college campuses has grown in the past 40 years from that of “glorified custodians” to full-fledged police officers, often with powers to search, detain, arrest, and even to use deadly force. Yet most state open records laws have not kept up, failing to require disclosure of records about crimes reported to or arrests made by sworn police officers at private universities. This article provides a full national picture by identifying the statutes and analyzing the cases to address whether state open records laws apply to private university police. It then suggests that the “functional equivalency test” provides courts a method to require transparency at these police departments.

Analisis Faktor Kepuasan Pengguna Layanan Website SKCK Online Menggunakan Metode End User Computing Satisfaction (EUCS)

One of the main duties of the police is to provide services to the community, namely the preparation of Police Record Certificate (SKCK). Making SKCK based online to facilitate the community in making SKCK. But there are some online SKCK users, there are still many problems that arise and criticism of online SKCK. Therefore it is necessary to measure the level of satisfaction and analyze the factors that affect user satisfaction with online SKCK. This study uses the End User Computing Satisfaction (EUCS) method. This type of research is quantitative by distributing questionnaires to SKCK registrants in the Banyuwangi area. Data analysis was carried out by using valid test, reliable test, descriptive statistical test, F test and T test using SPSS 22. The results of the descriptive test with the Likert scale in order of the largest, namely the content variable with a percentage of 85.4%, are included in the Very Satisfied category, the 80.4% timeliness variable is included in the Very Satisfied category, the 75.8% ease of use variable is included in the Satisfied category, the 73.2% format variable is included in the Satisfied category and 67.5% accuracy variable is included in the Satisfied category.

Motivational Strategies in Interventions for Intimate Partner Violence Offenders: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Previous research suggests that the inclusion of motivational strategies in interventions for intimate partner violence (IPV) offenders could increase their effectiveness. This review evaluated the effectiveness of interventions for IPV offenders that includes motivational strategies to reduce physical and psychological IPV, treatment dropout, official recidivism to IPV offending, and to increase intervention attendance dose. The present systematic review and meta-analysis were conducted using PRISMA guidelines. The following databases were searched from 1983 to 2018 for randomized controlled trials (RCTs) of interventions for IPV offenders that incorporated motivational strategies for adult participants that included men and included IPV behaviors as outcomes: Cochrane Collaboration, MEDLINE, EMBASE, PsycINFO and CINAHL. A total 1,134 studies were identified, 12 RCTs were included in the narrative review and 7 in the meta-analysis. Results indicated that IPV interventions that incorporated motivational strategies were significantly more effective in increasing the intervention dose and reducing dropout than interventions without motivational strategies. IPV offenders receiving interventions with motivational strategies were 1.73 times less likely to intervention dropout compared to those in interventions without such strategies. For physical and psychological IPV and official recidivism (e.g., rearrests, police record), evidence favored interventions with motivational strategies, although not significantly. These findings have important practical implications, especially considering the high dropout rates in IPV offender programs and the link between dropout and higher rates of recidivism.

Políticas de selección y contratación de personal en la alcaldía municipal de Puerto Cabezas

En esta investigación se han analizado las políticas de selección y contratación de personal de la alcaldía municipal de Puerto Cabezas, en cuanto la selección del personal conlleva al éxito de la empresa mediante la formación de recursos humanos que sean capaces de cumplir con las tareas asignadas. La metodología fue de tipo cualitativo, descriptivo, retrospectivo y de corte transversal; en el cual se aplicó entrevistas a personas claves y a los trabajadores de la alcaldía municipal.Los resultados obtenidos muestran que los principales factores que inciden en las políticas de selección y contratación del personal son: amistades, lineamiento o influencia político (aval político), experiencia laboral en algunas áreas, record de policía y el nivel académico. Asimismo, en la alcaldía municipal existe política de selección y contratación de personal, pero que no lo implementa de conformidad a lo establecido en la ley de contratación pública.