While the Nordics have long acted as champions of gender equality, there is still a need for a more nuanced understanding of gendered differences in safety and well-being. A large body of research on masculinity and fear has found men to express fear in public space to a lesser extent than women, perpetuating a notion of men as ‘fearless’. In this study, we challenge this notion by seeking a better understanding of men's overall fear of victimization as well as how fear impacts their behavior where they live, in relation to places, people, and everyday routines. Using statistical methods, chi-square analysis and binary logistic regression, we investigate the nature of men's fear and the effect fear has on their lives using 20,781 answers from the 2020 Stockholm Safety Survey. Findings indicate that while men are generally less fearful than women, intersections between respondents' gender, income level, and ethnic background show a complementary picture. Foreign-born and low-income resident men expressed similar or even higher levels of neighborhood fear than women. Additionally, the drivers of men's general fear of crime and neighborhood-related fear were found to differ, where results for Swedish-born and foreign-born men show opposing patterns for each measure. Men who live in neighborhoods with more physical disorder and low social cohesion are also more likely to avoid places and engagement with people where they live, as well as changing routine activities. The paper finishes with recommendations for future research.

Although the influence of the built environment on both crime and people’s safety perceptions is well documented in the international literature, less evidence is found regarding the link between urban safety perceptions and crime occurrence. In this article, we investigate the potential relationship between crime and visual perceived safety (VPS), using Stockholm, Sweden as a case. Central to the study is the VPS score, a detailed measure of VPS and situational fear, created by combining a deep learning model with a data set of local street view images and citizen impressions. We examine this measure together with traditional crime records to compare the city’s distribution of safety and crime. First, geographical patterns and spatial clusters of high and low levels of crime and VPS were detected. Then, drawing from principles of environmental criminology, a spatial regression was used to examine the relationship between the VPS score and crime, controlling for sociodemographics and land-use factors. Findings show that crime rates of different types are significant predictors of poor VPS, but mismatching geographies of perceived safety and crime are common. The article discusses the findings and finishes by highlighting the impact of these results for research and practice.

This study examines the concentration of crime at residential buildings and investigates whether housing ownership has an impact on such a concentration. Using Geographic Information Systems (GIS), police-recorded crime data were geocoded at the building level and combined with socio-demographic and land use variables in Poisson regression models. The results indicate that a small percentage of buildings is responsible for a large proportion of crimes. This pattern persists even after offences are standardised by the number of apartments. Buildings under private housing ownership are generally associated with lower crime levels than those under rental; however, this relationship is not uniform across private housing companies and different types of crime. Findings point to the need for further research into how building-level management practices interact with neighbourhood-wide policing strategies and other micro-level factors, such as a building’s design, location, and accessibility, in shaping crime outcomes.

Perceived neighborhood safety significantly affects the quality of life and social cohesion of communities. However, the perspectives of non-residents are often neglected, despite their potential influence on local views. This study addresses this gap by examining how locals (residents and frequent visitors) and outsiders (non-visitors) perceive safety in the largely stigmatized Stockholm district of Järva. We use a digital participatory mapping tool that allows citizens to share safety perceptions and experiences of victimization interactively. Surveying 592 respondents and using a mixed-methods approach, the study investigates the environmental, social, and emotional factors shaping these perceptions. Findings highlight how stigma, place attachment, and familiarity play an important role in moderating safety concerns, as even minor first-hand experience with Järva was linked to improved neighborhood perception. The study concludes by reflecting upon the importance of addressing territorial stigma and promoting local engagement to improve local and outsider safety perceptions.

Cities are complex, dynamic and constantly evolving systems, shaped by a plethora of factors that in turn significantly impact our individual safety. These factors are embedded in everything from the physical design of urban settings to the social interactions and activities that take place within them. Compared to other urban challenges such as crime, perceived safety and fear are more abstract and subjective phenomena that are much more difficult to define, understand and not to mention prevent. The aim of this thesis is to examine how perceived safety can be conceptualized and measured in urban environments in order to enhance the accuracy and comprehensiveness of urban safety diagnostics. The approaches of the studies explore both more traditional methods of surveys, regression models and spatial analysis, as well as more emergent methodologiesof the past few decades, such as deep learning models and mobile app data collection. The studies include analyses of perceived safety on multiple levels, from meso- to microlevel, comparisons of residents and non-residents, as well as intersectional analyses of gender, age, ethnicity, and income. The findings of the thesis highlight how various conceptualizations of perceived safety and methodologies used to measure them reveal different understandings. Local and global measures of fear have inverted relationships with marginalized men in Sweden, who, in contrast to common beliefs, express similar levels of poor neighborhood safety to women overall. Spatial and conceptual contrasts were identified between survey-based measures of neighborhood safety, objective safety measures such as crime rates, and safety scores generated by deep learning models. A survey based on a public participation geographic information system (PPGIS) revealed the moderating effect of place familiarity and place stigma, where minor differences in neighborhood familiarity were found to significantly affect perceptions. Mobile app data collection was also found to be a potential way to capture highly spatio-temporally detailed data on perceived safety, while retaining the ability to capture personal narratives and emotional connections to place. The thesis concludes with a reflection of implications and practical insights of the findings for researchers, urban planners, and policymakers, encouraging strategies for more comprehensive diagnostics of safety. 

Städer är komplexa, dynamiska och ständigt föränderliga system, formade av en mängd olika faktorer som i sin tur har en betydande inverkan på vår individuella trygghet. Dessa faktorer är inbäddade i allt från den fysiska utformningen av urbana miljöer till de sociala interaktioner och aktiviteter som äger rum inom dem. Jämfört med andra urbana utmaningar såsom brottslighet är upplevd trygghet och rädsla mer abstrakta och subjektiva fenomen som är mycket svårare att definiera, förstå och inte minst att förebygga. Syftet med denna avhandling är att undersöka hur upplevd trygghet kan konceptualiseras samt mätas i urbana miljöer för att förbättra träffsäkerheten och omfattningen av trygghetsdiagnostik i städer. Angreppssätten i de inkluderade studierna omfattar både mer traditionella metoder såsom enkäter, regressionsmodeller och geografiska analyser, men även nyare metoder från de senaste decennierna såsom djupinlärningsmodeller (deep learning-modeller) och datainsamling via mobilapplikationer. Studierna inkluderar analyser av trygghet på flera nivåer, från meso- till mikronivå, jämförelser mellan boende och icke-boende, samt intersektionella analyser av kön, ålder, etnicitet och inkomst. Avhandlingens resultat belyser hur olika konceptualiseringar av upplevd trygghet och de metoder som används för att mäta dem ger upphov till olika förståelser. Lokala och globala mått på rädsla visade omvända samband för marginaliserade män i Sverige, vilka uttrycker – i motsats till rådande uppfattningar – liknande nivåer av otrygghet i sina bostadsområden som kvinnor i stort. Geografiska och konceptuella kontraster identifierades mellan enkätbaserade mått på trygghet i bostadsområden, objektiva säkerhetsmått såsom brottsstatistik, samt trygghetspoäng genererade av djupinlärningsmodeller. En enkät baserad på PPGIS (Participatory Public Geographic Information System) visade på den modererande effekten av platsbekantskap och platsrelaterad stigma, där små skillnader i kännedom om området hade stor påverkan på trygghetsuppfattningen. Datainsamling med hjälp av en mobilapplikation visade också potential att fånga in mycket detaljrik rumslig och tidsmässig data om upplevd trygghet, samtidigt som den möjliggör insamling av personliga berättelser och känslomässiga band till platsen. Avhandlingen avslutas med en reflektion kring implikationer och praktiska insikter av resultaten för forskare, stadsplanerare och beslutsfattare, med en uppmaning till strategier för mer heltäckande trygghetsdiagnostik.

This article investigates what causes an urban environment to be perceived as safe using Stockholm, the capital of Sweden, as the study area. The study integrates AI-generated safety scores from street view images, image segmentation techniques and conventional and crowdsourced data using Geographical Information Systems (GIS) and regression models. After accounting for income, crime and other area characteristics, the models reveal that areas with lower safety scores primarily consist of areas with a relatively large percentage of roads in industrial and/or interstitial mixed residential areas. Conversely, higher safety scores are found in large but distinct combinations of buildings, vegetation and open sky, from detached single-family housing to inner city high-density built areas. To enhance safety in an area, good contextual knowledge of the area is fundamental to prioritize interventions in interstitial mixed residential zones where roads and highways may be the dominant features.

In this study, we investigate whether fear of animal rights activism has animpact on farmers and, more specifically, critically assess farmers’ agencyby showing ways they cope with this fear. The analysis is based onanswers from a survey of 3,815 animal farmers in Sweden in 2020. Chisquareanalyses, logistic regression models, and Geographical InformationSystems (GIS) underlie the methodology of the study. Fear of animal rightsactivism is perceived by farmers as having a negative impact on theirchildren’s wellbeing, their economic situation, and their quality of life andhaving led to reduced trust in strangers. While a fifth of respondentsdeclare they protect themselves against criminal acts, we discuss possiblereasons farmers prefer not to take action against potential threats.

The safety perception of the built environment, rather than the sheer number of crimes and incivility behavior, is a fundamental driver of public policies intended to improve urban safety. Traditional surveys often capture neighborhood residents’ perceived safety, but may not fully reflect the perceptions of people who are unfamiliar with the area. In this study, focused on the city of Stockholm, Sweden, we develop a geospatial artificial intelligence (GeoAI) approach using street view images and recruiting locals to create a measure of citywide residents’ safety perceptions. We compare the measures from the survey based on neighborhood residents’ responses with those from the GeoAI approach to better understand the relationship between these safety measures. We model the two forms of safety perceptions and their disparities (i.e., perception bias) as a function of the city’s land use and its socio-demographics. Results confirm that while the GeoAI-based measures better capture people’s instant impressions of the built environment across the city, the survey-based measures reflect their overall daily experiences of specific areas. Regions that appear to be economically vibrant and have inner-city streetscapes are perceived as safe places from visual appearance but are not always perceived as such by residents. Older adults tend to overestimate their likelihood of being victimized by crime, which may enlarge perception bias. The study concludes by critically assessing the potential ethical issues (e.g., spatial bias, population bias) in the proposed methodology and making suggestions for future research.

This article explores the nature and frequency of crimes and people's safety perceptions in rural areas using a systematic review of the literature. It explores four decades of English-language publications on crime and safety in rural areas from several major databases; mainly Scopus, JSTOR and ScienceDirect. The number of retrieved documents was 840, of which 410 were selected for in-depth analysis and their topics later categorized by theme. We found that rural crime research took off after the mid-1980s and experienced an increase during the 2010s. Despite the domination by North American, British and Australian scholarship, studies from other parts of the world (including the Global South) are increasingly being published as well. Publications on rural crime patterns (e.g., farm crime) compose over one-fifth of the reviewed literature. This together with rural policing/criminal justice and violence constitute the three largest themes in rural criminology research. With ever-increasing links between the local and the global, this review article advocates for tailored multilevel responses to rural crimes that, more than ever, are generated by processes far beyond their localities.

Conflicts between animal production and animal rights activism are becoming more common in a number of countries, including Sweden. Although most animal rights advocates would not consider committing a crime, there have been numerous accounts in which farmers have been victimized because they are animal producers. This study investigates the extent and characteristics of crimes committed against animal farmers and their families. The analysis is based on answers from a survey of 3,815 animal farmers in Sweden in 2020. Cross-table analysis, logistic regression models, and geographical information systems (GIS) underlie the methodology of the study. One in eight respondents declared being exposed to crimes because they are animal producers (from thefts, trespassing, sabotage, and threats to physical violence, most face-to-face but also online), but 60 percent of the victims never report to the police. Among nonvictims, half of the respondents knew someone who had been a victim of crime. Findings indicate that farmers’ victimization for theft or robbery show different motivations than those that are directed at them because they work with animal production. These findings highlight the importance of incorporating farmers’ safety needs into sustainable rural development policies.