Service Calls Research Articles

Non‐Status Citizenship and the Paradoxes of Immigration Regimes in a Sanctuary City

AbstractNon‐status people face a socio‐legal precariousness that contradicts the promises of an inclusive city. Marking Toronto's tenth anniversary of its “sanctuary city” policy, our research assesses the progress and potential of social planning and municipalist agendas to support irregularised residents. Drawing from interviews with service providers, city officials, and non‐status citizens in Toronto, we propose a decolonial politics of urban citizenship recognition we call “non‐status citizenship”. This concept addresses specific paradoxes related to irregularisation, access, jurisdiction, and regularisation. By framing our discussion around these paradoxes, we highlight the discomfort and transformative potential of non‐status citizenship for immigration regimes in sanctuary cities. We argue that recognising non‐status citizenship goes beyond notions of urban citizenship to claim formal recognition and security, which resolves the four paradoxes theoretically, politically, and practically. We also emphasise the role of cities in expanding service delivery and calling out the failure of planning across levels of government.

“I think we should wait and see”: A qualitative study of call-takers’ decision-making in consultations with patients suffering unrecognized myocardial infarction

ObjectivesCall-takers face a complex situation when assessing medical problems in emergency medical services calls. Patients with myocardial infarction experiencing atypical symptoms risk misinterpretation. We examined development in call-takers' decision-making process in telephone consultations with patients having imminent myocardial infarction. MethodsRecording of 38 calls among 19 patients (two per patient) who contacted Copenhagen Emergency Medical Services (Denmark) at least twice within one week before myocardial infarction diagnosis. The penultimate and last call were compared using qualitative content analysis. ResultsCall-takers’ assessment of the condition changed from symptom picture and dismissal of heart disease in penultimate call to severe condition, not heart-related, and possible heart disease in last call. Call-takers recommended watchful waiting in the penultimate call. Both calls involved response negotiation, while caution regarding misinterpretation was only seen in the penultimate call. ConclusionCall-takers used different decision-making approaches when the caller’s symptom descriptions appeared unclear and not corresponding with the medical understanding of severe conditions. Call-takers did not negotiate the condition's assessment but engaged in discussions about the response choice. Practice implicationsA protocol to negotiate response choice with callers having unclear clinical conditions should be developed. Clarifying watchful waiting as a recommendation may assist call-takers’ decision-making.

Mindful Transportation: A Conceptual Framework for Enhancing Accessibility for People with Disabilities in Malaysia

This conceptual paper explores the integration of mindfulness principles into the development of transportation services for people with disabilities (PWDs) in Malaysia. Transportation plays a critical role in promoting inclusivity and enhancing the quality of life for PWDs, yet accessibility remains a significant challenge due to infrastructural barriers, lack of awareness, and limited empathy from service providers. Drawing on the concepts of mindfulness, which are rooted in awareness, empathy, and responsiveness, this paper proposes a framework that emphasizes inclusivity, respect, and collaboration among key stakeholders. The proposed framework emphasizes the need for a holistic approach that incorporates physical accessibility, staff training, and policy reforms. Inclusivity involves modifying infrastructure to meet universal design standards, while empathy requires transport providers to understand the unique challenges faced by PWDs and offer compassionate, tailored services. Responsiveness, a key element of mindfulness, calls for flexible and adaptive transport services that cater to the real-time needs of PWDs, ensuring that they can access public transportation with ease and dignity. By applying this mindful approach, the transportation system can become more accommodating and respectful toward PWDs, thereby reducing social exclusion and improving their mobility. This paper contributes to the growing body of literature on disability inclusion and provides actionable strategies for policymakers, transport providers, and disability organizations to work together in creating a more accessible public transportation system. Future research should investigate the practical application of this framework and its potential to drive policy changes that benefit PWDs across Malaysia.

Community Paramedicine Program in Social Housing and Health Service Utilization

Community Paramedicine at Clinic (CP@clinic) is a chronic disease prevention program that decreases 911 calls for emergency medical services, but its wider system effects are unknown. To evaluate the effects of CP@clinic vs usual care on individual-level health service utilization outcomes. This open-label, pragmatic cluster randomized clinical trial evaluated all residents 55 years or older in 30 social housing buildings in Ontario, Canada, that had (1) a unique postal code, (2) at least 50 apartments, (3) 60% or more residents 55 years or older, and (4) a similar building for pairing (15 intervention and 15 control buildings, pair-matched randomization). The 12-month intervention had a staggered start date from January 1, 2015, to December 1, 2015, and ended between December 31, 2015, and November 30, 2016. Administrative health data analysis was conducted in May 2022. CP@clinic was a health promotion and disease prevention program led by specially trained community paramedics who held weekly drop-in sessions in social housing buildings. These paramedics conducted 1-on-1 risk assessments, provided health education and referrals to relevant community resources, and, with consent, sent assessments to family physicians. Control buildings received usual care (universal health care, including free primary and specialty medical care). Individual-level health service utilization was measured from administrative health data, with ED visits via ambulance as the primary outcome; secondary outcomes included ED visits for any reason, primary care visits, hospitalizations, length of hospital stay, laboratory tests, receipt of home care, transfer to long-term care, and medication initiation. Generalized estimating equations were used to estimate intervention effects on individual-level health service utilization, accounting for trial design and individual-level baselines. The 30 social housing buildings had 3695 residents (1846 control and 1849 intervention participants; mean [SD] age, 72.8 [9.1] years; 2400 [65.0%] female). Intention-to-treat analysis found no significant difference in ED visits by ambulance (445 of 1849 [24.1%] vs 463 of 1846 [25.1%]; adjusted odds ratio [AOR], 0.97; 95% CI, 0.89-1.05) but found higher antihypertensive medication initiation (74 of 500 [14.8%] vs 47 of 552 [8.5%]; AOR, 1.74; 95% CI, 1.19-2.53) and lower anticoagulant initiation (48 of 1481 [3.2%] vs 69 of 1442 [4.8%]; AOR, 0.68; 95% CI, 0.53-0.86) in the intervention arm vs the control arm. CP@clinic attendance was associated with higher incidence of primary care visits (adjusted incidence rate ratio, 1.10; 95% CI, 1.03-1.17), higher odds of receiving home care (AOR, 1.07; 95% CI, 1.01-1.13), and lower odds of long-term care transfers (AOR, 0.32; 95% CI, 0.13-0.81). In this cluster randomized clinical trial of CP@clinic, the intervention did not affect the rate of ED visits by ambulance; however, there were increased primary care visits and connections to home care services, which may have increased antihypertensive medication initiation and reduced long-term care transfers from social housing. Health policymakers should consider CP@clinic's impact as an upstream approach to improve care for older adults with low income. ClinicalTrials.gov Identifier: NCT02152891.

Challenges and Solutions in Testing Mainframe Applications in Modern Banking

Because the foundation of their operations is still housed in legacy systems, banks continue to use them. Banks must modify their systems to remain competitive in light of the swift changes in technology and customer needs. Mainframe systems have been an integral part of corporate computing for many years, enabling critical applications across a range of industries, including banking, retail, and healthcare. There is rising interest in leveraging Application Programming Interfaces (APIs) to expose these old apps' data and features, hence accelerating the construction of new applications and maximising their capability and enabling their reuse. Nonetheless, there are several obstacles to overcome in the process of locating and making available APIs for various business use cases. In this study, we examine the difficulties involved in developing APIs for mainframe systems that are no longer in use and suggest a unique architecture to enable communication for a range of use cases. We performed a qualitative poll with nine mainframe developers, whose average experience was fifteen years, to evaluate the efficacy of our methodology. We were able to determine which APIs were candidates and how long it would take to implement them for two industry mainframe applications and the public mainframe application GENAPP thanks to the poll. We create a list of artefacts, such as screens, transactions, business rules, inter-micro service calls, control flow blocks, and data accesses, in order to identify APIs. IBM Watsonx Code Assistant for Z Refactoring Assistant includes an implementation for computing API signatures. We proved the practicality of our technique by running the discovered APIs on an IBM Z mainframe system to assess their accuracy.

Renting trouble? An analysis of crime and calls to police at addresses with different rental types

BackgroundThe number of studies about crime at short-term rentals (STRs), and about crime concentration has surged in recent years, but few have bridged these literatures. This study examines crime and calls for service at STRs in relation to other rentals, hotels, and all other addresses in a university city.MethodsPolice circumstances, rental properties, hotels and motels, liquor licenses, and all other addresses are assessed from January 2021 through June 2023 to understand public safety at STRs compared to other address-types.ResultsSTRs make up less than 10% of rental addresses. Police circumstances are significantly and negatively associated with both distance to campus and to liquor licenses. The maximum unrelated occupancy is positively and significantly associated with issues. STRs have greater issues for their lower maximum occupancy, but other rentals and hotels present substantially more problems on a per-address basis.ConclusionThese findings highlight the scope of STR circumstances, clarify potential differences in crime versus calls for service, and suggest that on a per-address basis, both are substantially worse at hotels and longer rentals than STRs.

Enhancing Machine Learning-Based Autoscaling for Cloud Resource Orchestration

Performance and cost-effectiveness are sustained by efficient management of resources in cloud computing. Current autoscaling approaches, when trying to balance between the consumption of resources and QoS requirements, usually fall short and end up being inefficient and leading to service disruptions. The existing literature has primarily focuses on static metrics and/or proactive scaling approaches which do not align with dynamically changing tasks, jobs or service calls. The key concept of our approach is the use of statistical analysis to select the most relevant metrics for the specific application being scaled. We demonstrated that different applications require different metrics to accurately estimate the necessary resources, highlighting that what is critical for an application may not be for the other. The proper metrics selection for control mechanism which regulates the requried recources of application are described in this study. Introduced selection mechanism enables us to improve previously designed autoscaler by allowing them to react more quickly to sudden load changes, use fewer resources, and maintain more stable service QoS due to the more accurate machine learning models. We compared our method with previous approaches through a carefully designed series of experiments, and the results showed that this approach brings significant improvements, such as reducing QoS violations by up to 80% and reducing VM usage by 3% to 50%. Testing and measurements were conducted on the Hungarian Research Network (HUN-REN) Cloud, which supports the operation of over 300 scientific projects.

A quasi-experimental evaluation of RADAR: response awareness, de-escalation, and referral for people with behavioral health issues

ABSTRACT This paper describes the implementation and evaluation of RADAR (Response Awareness, De-Escalation, and Referral), a hybrid CIT/co-response program for people with behavioral health issues (PBHI). RADAR emphasized information sharing between police, PBHI, and behavioral health professionals and targeted outreach to PBHI by a police officer and clinician working in partnership. We evaluated RADAR using a quasi-experimental analysis of calls for service and incident data, an officer survey, and interviews with key personnel. While RADAR did not significantly reduce calls, incidents, or physical contact and resistance relative to a comparison jurisdiction, the survey and interviews suggest that it did help to shift the department’s culture and organizational perceptions around collaborative responses to PBHI. The practical implications of our findings for police agencies seeking to implement co-responder programs include the need to focus on sustainability; relationship building between the police, PBHI, and clinicians; and technological solutions to improve data collection and evaluation efforts.

A spatial analysis of mental health-related calls for service in Atlantic City, New Jersey

ABSTRACT Objective Police officers often find themselves responding to calls that do not involve criminal behavior, but calls related to individuals experiencing emotional distress or mental illness that requires police response. This research aims to identify high-risk places of mental health calls for service (MHCFS) in an urban setting and compare place features of these locations by police response (locations where a CIT-trained officer is dispatched versus a non-trained officer dispatched). Data/Methods Our research uses Atlantic City Police Department’s calls for service data from 1 January 2019 through 30 December 2022, including the incidents of mental incompetence with location components. After removing the calls that were not coded as mental health, a total of 2229 incidents involving perceived mental illness were geocoded and compared. We used RTMDx software to generate risk terrain models for MHCFS in Atlantic City, NJ. Findings The RTM analysis yielded no association between places of interest and MHCFS for calls involving non-CIT-trained officers. Yet, we identified five high-risk activity spaces of MHCFS where officers with CIT training were involved. Grocery stores (RRV = 2.873), places of leisure (RRV = 2.764), Health & Wellness Facilities (RRV = 2.624), Eateries & Restaurants (RRV = 2.547), and Convenience & Variety Stores (RRV = 2.280) are the risk factors identified by the RTM analysis. Given the characteristics of places identified by risk-terrain modeling, we reason that the characteristics of these places indicate that individuals experiencing perceived or actual mental health problems hang out in spaces with ease of access and in spaces where they can stay relatively longer with minimal attention. Conclusion Our research suggests that there is an association between spatial factors and MHCFS that are responded to by CIT-trained officers. City officials should consider deploying additional resources and mental health staff to these places to address the issue of mental health in urban settings. Future research should consider testing whether the places we identified in our analysis are also high-risk places for MHCFS in other urban environments.

Imagining Future Human-centred AI

The rapid growth in the development of AI-enabled and intelligent systems and services calls for more serious and urgent attention to human-focused and human-centred principles, methods, and approaches. This paper reports on a study of recent human-centred AI research literature to examine the extent to which the three principles of safety, trustworthiness, and reliability have been addressed in recent AI publications.

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A Multi-Method Data Science Pipeline for Analyzing Police Service

Despite the fact that most police departments in the U.S. serve jurisdictions with fewer than 10,000 residents, policing practices in small towns are understudied. This is due in part to data limitations and technological barriers that exist in the small-town context. In this article we focus on one small town police department in New England with a history of misconduct, and develop a comprehensive data science pipeline that addresses the stages from design and collection to reporting. We present the reader with specific tools in the open-source Python ecosystem for replicating this pipeline. Once these data are processed, we perform two statistical analyses in an attempt to better understand the provisions of service by the small-town police department of focus. First, we perform ecological inference to estimate the rate at which residents are placing calls for service. Second, we model wait times using a negative binomal regression model to account for overdispersion in the data. We discuss data and model limitations arising through the pipeline creation and analysis process.

Intelligent risk management: natural language processing real-time triage of police calls for service

ABSTRACT Can an intelligent call center improve the deployment of a safe and effective diversified response (e.g., differential police response, coresponse and Alternate First Responders)? This article examines a proof-of-concept intelligent call center for enhanced 911 call processing, at the City of Seattle (Washington, USA). This study employed common commercial technology to 1) transcribe incoming 911 call audio, 2) render a real-time forecast of call risk and 3) visualize the results for personnel handling the call as “intelligent decision support.” This project proves a “human-inthe- loop” application of Machine Learning (ML) can support the professional judgement of experienced human operators with a precise, low-latency forecast of call risk. Further, the demonstrated system is designed to learn. As a diversified response system evolves, statistical feedback is incorporated using the Risk Managed Demand framework. Implications for risk management, the opportunity for diversified response, and the ethics of ML are discussed.

Moving Beyond Referrals: Addressing Multilevel Barriers to Substance Use Treatment Engagement Through Police-Led Recovery Management Check-Ups.

The opioid epidemic in the United States (US) has prompted innovative responses from law enforcement agencies including specialized units to refer overdose survivors to substance use treatment following an overdose. However, traditional law enforcement outreach does not address the multilevel barriers to treatment engagement that lead to repeat overdose-related calls for service. The current evaluation explored the process components and outcomes of a Comprehensive Opioid Abuse Program (COAP) initiative within a local law enforcement agency in the Southeast US. COAP funding supported a police-led recovery management team (RMT) to connect overdose survivors to substance use treatment. The RMT also utilized recovery management check-ups (RMCs) to provide sustained support to enhance substance use treatment engagement beyond the initial treatment referral. A mixed-methods approach was employed to examine participant demographic, substance use, mental health, treatment, and criminal justice characteristics (N = 65) and explore perceptions of programmatic strengths and potential areas for improvement (N = 15). The quantitative and qualitative analyses were informed by the Recovery Capital Model. Quantitative analysis revealed that the RMT connected many participants with various support services, notably including housing assistance and health insurance. Qualitative findings highlight program effectiveness in improving social, community, and personal recovery capital. These findings contribute to expanding research on police-led post-overdose initiatives and suggest that police-led RMCs can address multilevel barriers to treatment engagement and minimize law enforcement stigma.

Firearm shootings and the police response: examining the impact of gunshot detection technology

ABSTRACT This study explores the impact of gunshot detection technology (GDT) in Denver, CO, Milwaukee, WI, and Richmond, CA on officer workload and response times to firearm shooting notifications. All three departments experienced a twofold increase of being alerted to shooting incidents following GDT implementation, leading to a two- to threefold increase in staff time allocated to responding to these incidents. Response times to specific events were generally quicker for GDT alerts compared to traditional 911 calls for service regarding shots heard events. However, the time savings are primarily from the duration between notification and assignment of an officer, rather than the actual time taken by officers to arrive at the scene after being assigned. Insights from 46 stakeholder interviews offer optimal approaches for investigating shooting notifications and GDT program management. While GDT programs effectively reduce response times, agencies must anticipate increased workloads and implement specific program characteristics for optimal effectiveness.

Diverting 911 calls: Lessons from early adopting urban jurisdictions

AbstractResearch SummaryTwo perceptions drive interest in finding ways of diverting more 911 calls from police to civilian first responders: (1) police responses can result in inadvertent harm to citizens and (2) many calls to which police respond require services that police often cannot provide. Thus, using other personnel may improve police–citizen relations and strengthen crime fighting by reducing extraneous police burden. Using a case study design, we conducted formative evaluations of programs that have developed beyond pilots in three large U.S. cities: Albuquerque, Atlanta, and Houston. In each city, we interviewed officials, program operators, and other stakeholders and reviewed program documents and statistics. We detail the events and forces that led to the establishment of each program, the way in which the programs have been institutionalized, and the way they interact with the Police Department. We then discuss key lessons learned for these jurisdictions.Policy ImplicationsMany U.S. cities are considering diverting some emergency calls for service from police to civilian first responders. This analysis provides evidence to aid policy makers, researchers, and other stakeholders in the development and evaluation of community responder programs. In all respects, we find that cities’ unique experiences inform program design. For example, in Albuquerque, a City Hall‐driven initiative established a new city agency parallel to the Police Department. In Atlanta, decarceration activists drove the initiative; the program is a city/county‐funded nonprofit, more fragile in its funding. Risk aversion among call takers and dispatchers has led to low call diversion rates across all sites, but training and collaboration have shown promise to resolve this problem. Public safety officials external to the diversion programs commonly expressed concerns about first responder safety and perceptions that police are expected when 911 is called. This risk aversion has led to slower‐than‐expected expansion of the program within each city.

Space-Time Association between Gunshot Detection Alerts, Calls for Service, and Police Enforcement in Chicago: Differences Across Citizen Race and Incident Type

Space-Time Association between Gunshot Detection Alerts, Calls for Service, and Police Enforcement in Chicago: Differences Across Citizen Race and Incident Type

Space-Time Association between Gunshot Detection Alerts, Calls for Service, and Police Enforcement in Chicago: Differences Across Citizen Race and Incident Type

Abstract Objectives This study explores the level to which Gunshot Detection Technology (GDT) leads to increased arrests and stops as compared to shots fired calls for service (CFS) in Chicago, Illinois. Methods A two-process Knox test and point process test are applied to measure the level to which GDT alerts and CFS cluster with arrests and stops in space and time. Both tests are first applied to the aggregate arrest and stops data. We then disaggregate arrests and stops by type as well as suspect race/ethnicity to measure any disproportionate effects across GDT and CFS. Results Both GDT alerts and CFS are significantly associated with arrests and stops occurring in close spatial and temporal proximity. The relative effect of GDT and CFS was consistent across race in the majority of instances. The small number of instances with disparate effects did not exhibit any clear patterning. For some racial groups and arrest/stop types, GDT was associated with heightened enforcement while CFS had a null effect, with the opposite relationship observed for other racial groups and arrest/stop types. Conclusions Overall, the results indicate that GDT systems may not generate racial disparities in arrests and stops above and beyond what results from the standard police response to gunfire. Racial disparities resulting from police responses to reported gunfire likely relate to aspects of the reporting and dispatch processes generally rather than as they relate specifically to GDT.

제미나이 출범에 따른 글로벌 주요 항만의 영향 분석

Purpose : The purpose of this study is to analyze the representative differences between the services implemented by the launch of the Gemini alliance and the existing alliance services. Additionally, it forecasts the impact of the Gemini launch on Busan Port and other top 20 global ports. Research design, data and methodology : An empirical analysis is conducted using data from the Gemini alliance and the top 20 global ports. Specifically, the analysis derives the impact on ports by utilizing the representative differences of the Gemini service, such as the size of the ships and the frequency of regular service calls, including GDP. Results : All three independent variables (ship size, frequency of regular service calls, and GDP) were found to have a significant impact on port throughput. In particular, the size of the ships and the frequency of regular service calls have a relatively greater impact compared to GDP. Conclusions : The frequency of regular service calls by Gemini at Busan Port is expected to decrease significantly, raising concerns about a potential reduction in Busan Port's throughput. However, considering the increase in the size of feeder ships and Gemini's market share of 20%, it is deemed unlikely that Busan Port's throughput will immediately decrease significantly due to the Gemini launch. Therefore, the success of the differentiated services promoted by Gemini is crucial.

Prediction of the future number of fall-related emergency medical services calls in older individuals

BackgroundFalls among older individuals contribute significantly to the rise in ambulance transport use. To recognize the importance of future countermeasures, we estimated the projected number and percentage of fall-related emergency medical service (EMS) calls.MethodsWe examined the sex, age group, and location of falls among patients aged ≥ 65 years who contacted emergency services in Sapporo City from 2013 to 2021. Annual fall-related calls per population subgroup were calculated, and trends were analyzed. Four models were used to estimate the future number of fall-related calls from the 2025–2060 projected population: (1) based on the 2022 data, estimates from the 2013–2022 data using (2) Poisson progression, (3) neural network, (4) estimates from the 2013–2019 data using neural network. The number of all EMS calls was also determined using the same method to obtain the ratio of all EMS calls.ResultsDuring 2013–2022, 70,262 fall-related calls were made for those aged ≥ 65 years. The rate was higher indoors among females and outdoor among males in most age groups and generally increased with age. After adjusting for age, the rate increased by year. Future estimates of the number of fall calls are approximately double the number in 2022 in 2040 and three times in 2060, with falls accounting for approximately 11% and 13% of all EMS calls in 2040 and 2060, respectively.ConclusionThe number of fall-related EMS calls among older people is expected to increase in the future, and the percentage of EMS calls will also increase; therefore, countermeasures are urgently needed.