Social Disorganisation and Feeling Safe: Insights from Diverse Scottish Neighbourhoods
Abstract
Neighbourhood safety remains a critical urban challenge, with social disorganisation theory positing that structural factors like poverty and residential instability weaken community cohesion and amplify crime perceptions. While Scotland has seen declining crime rates, persistent violence in deprived areas, and emerging disorder in affluent communities necessitate safety measures across socioeconomic situations. This study examines how social disorganisation influences perceptions of safety across affluent and deprived neighbourhoods in Edinburgh and Glasgow, Scotland. Using a cross-sectional survey of 610 residents, we employed multiple regression and ANOVA models to analyse six key indicators of social disorder (noise, vandalism, verbal abuse, burglary, unsupervised children, and physical assault) against self-reported feelings of safety. Data were transformed using the Item Response Theory and Rasch Model to enable parametric analysis, with cross-validation confirming model robustness (R² > 0.92). Results revealed that verbal abuse (β = -0.565) and physical assault (β = -0.499) were the strongest predictors of reduced safety, with deprived areas exhibiting heightened vulnerability. Counterintuitively, affluent neighbourhoods reported higher perceived disorder for vandalism and unsupervised children, suggesting socioeconomic differences in reporting behaviours or tolerance thresholds. City-specific variations emerged: vandalism significantly impacted safety in Glasgow’s deprived areas but not Edinburgh’s, highlighting the need for locally tailored interventions. The findings reinforce social disorganisation theory while demonstrating its nuanced application across socioeconomic contexts. Urban safety research by incorporating minor incivilities often overlooked in crime statistics, offering evidence for holistic approaches to neighbourhood security.
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Atkinson, R. (2004). Neighbourhood boundaries, social disorganisation and social exclusion, 2001-2002. UK Data Archive.
Bilen, Ö., Aşkın, Ö. E., Büyüklü, A. H., Ökten, A., & Gür, M. (2013). How the fear of crime spatially differs among the districts of Istanbul? NWSA Academic Journals, 8(4), 153–164. https://doi.org/10.12739/NWSA.2013.8.4.3C0115
Brunton-Smith, I., Sutherland, A., & Jackson, J. (2013). The role of neighbourhoods in shaping crime and perceptions of crime. In D. Manley (Ed.), Neighbourhood Effects or Neighbourhood Based Problems? A Policy Context (pp. 67–87). Springer Netherlands. https://doi.org/10.1007/978-94-007-6695-2_4.
Camina, M. (2004). Understanding and engaging deprived communities. Home Office.
Courson, B., & Nettle, D. (2021). Why do inequality and deprivation produce high crime and low trust? Scientific Reports, 11(1). https://doi.org/10.1038/s41598-020-80897-8.
Danapriatna, N., Ismarani, I., & Dede, Moh. (2023). Application of biochar and biological fertilizer to improve soil quality and Oryza sativa L. productivity. Cogent Food & Agriculture, 9(1), 2207416. https://doi.org/10.1080/23311932.2023.2207416
De Pedro, K. T., Gilreath, T., & Berkowitz, R. (2016). A latent class analysis of school climate among middle and high school students in California public schools. Children and Youth Services Review, 63, 10–15. https://doi.org/10.1016/j.childyouth.2016.01.023
Dede, M. (2023). Multivariate analysis and modeling of shoreline changes using geospatial data. Geocarto International, 38, 2159070. https://doi.org/10.1080/10106049.2022.2159070.
Dede, M., Sugandi, D., & Setiawan, I. (2018). Pengaruh kondisi lingkungan terhadap kerawanan kejahatan di kawasan perkotaan studi kasus di Kecamatan Sumur Bandung, Kota Bandung. Seminar Nasional Geomatika, 3, 555–564. https://doi.org/10.24895/SNG.2018.3-0.1009
Fraser, A., & Gillon, F. (2023). The Glasgow miracle? Storytelling, violence reduction and public policy. Theoretical Criminology, 13624806231208432. https://doi.org/10.1177/13624806231208432.
Gomes, C. M. A. (2014). Formal-logic development program: Effects on fluid intelligence and on inductive reasoning stages. Journal of Education, Society and Behavioural Science, 1234–1248. https://doi.org/10.9734/BJESBS/2014/10757.
Goodall, C. A. (2019). Assault–related sharp force injury among adults in Scotland 2001–2013: Incidence, socio-demographic determinants and relationship to violence reduction measures. Aggression and Violent Behavior, 46, 190–196. https://doi.org/10.1016/j.avb.2018.10.002.
Holland, G. (1972). Rural crime prevention: Vandalism. In Division of Agricultural Sciences and Natural Resources. Oklahoma State University.
Hutta, J. S. (2009). Geographies of Geborgenheit: Beyond feelings of safety and the fear of crime. Environment and Planning D: Society and Space, 27(2), 251–273. https://doi.org/10.1068/d3308
Kean, J. (2018). An introduction to item response theory and Rasch analysis: Application using the eating assessment tool (EAT-10). Brain Impairment, 19(1), 91–102. https://doi.org/10.1017/BrImp.2017.31.
Krug, E. G. (2002). The world report on violence and health. Lancet (London, England, 360(9339), 1083–1088. https://doi.org/10.1016/S0140-6736(02)11133-0.
Krzywinski, M., & Altman, N. (2015). Multiple linear regression. Nature Methods, 12(12), 1103–1104. https://doi.org/10.1038/nmeth.3665.
Kubrin, C. E., & Mioduszewski, M. D. (2019). Social disorganization theory: Past, present and future. In M. D. Krohn (Ed.), Handbook on crime and deviance (pp. 197–211). Springer International Publishing. https://doi.org/10.1007/978-3-030-20779-3_11.
Kubrin, C., & Wo, J. (2015). Social disorganization theory’s greatest challenge. In The handbook of criminological theory (pp. 121–136). https://doi.org/10.1002/9781118512449.ch7.
Lee, V. W. P., Ling, H. W., & Xu, J. (2023). Inequality and deprivation in an affluent community: A case study of the livelihood of low-income households in Central and Western District, Hong Kong. SSRN. https://doi.org/10.2139/ssrn.4590593.
Liu, N. (2023). Mediating roles of perceived social support and sense of security in the relationship between negative life events and life satisfaction among left-behind children: A cross-sectional study. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1100677.
Lymperopoulou, K., & Bannister, J. (2022). The spatial reordering of poverty and crime: A study of Glasgow and Birmingham (United Kingdom), 2001/2 to 2015/16. Cities, 130, 103874. https://doi.org/10.1016/j.cities.2022.103874.
Mariano, J., Sibila, Ramos , M. R., Gerardo, F., Cunha, C. L., Girenko , A., Alexandersson, J., Stree, B., Lamanna, M., Lorenzatto, M., Mikkelsen, L. P., Bundgård-Jørgensen, U., Rêgo, S., & de Vries, H. (2022). Too old for technology? Stereotype threat and technology use by older adults. Behaviour & Information Technology, 41(7), 1503–1514. https://doi.org/10.1080/0144929X.2021.1882577
Markowitz, F. (2001). Extending social disorganization theory: Modeling the relationships between cohesion, disorder, and fear. Criminology, 39, 293–319. https://doi.org/10.1111/j.1745-9125.2001.tb00924.x.
Mason, P., Kearns, A., & Livingston, M. (2013). “Safe Going”: The influence of crime rates and perceived crime and safety on walking in deprived neighbourhoods. Social Science & Medicine, 91, 15–24. https://doi.org/10.1016/j.socscimed.2013.04.011.
Meyer, J. P. (2014). Applied measurement with jMetrik. Routledge. https://doi.org/10.4324/9780203115190
Morenoff, J. D., & Sampson, R. J. (1997). Crime and the spatial dynamics of neighborhood transition: Chicago, 1970-1990. Social Forces, 76(1), 31–64. https://doi.org/10.2307/2580317.
Nurbayani, S., Dede, M., & Malihah, E. (2022). Fear of crime and post-traumatic stress disorder treatment: Investigating Indonesian’s pedophilia cases. Jurnal Ilmiah Peuradeun, 10(1), Article 1. https://doi.org/10.26811/peuradeun.v10i1.657
Nurbayani, S., Dede, M., Utami, N., & Widiawaty, M. (2023). The implementation of COVID-19 health protocol: A higher students’ perspective. Geografia-Malaysian Journal of Society and Space, 19(1), Article 1. https://doi.org/10.17576/geo-2023-1901-14
Nurbayani, S., Dede, Moh., & Widiawaty, M. A. (2022). Utilizing library repository for sexual harassment study in Indonesia: A systematic literature review. Heliyon, 8(8), e10194. https://doi.org/10.1016/j.heliyon.2022.e10194
Onori, F. (2021). An adaptation of the food insecurity experience scale (FIES) for measuring food insecurity among women in socially-backward communities. Asian Journal of Agriculture and Development, 18(1), 66–82. https://doi.org/10.37801/ajad2021.18.1.5.
Porter, J. R., Rader, N. E., & Cossman, J. S. (2012). Social disorganization and neighborhood fear: Examining the intersection of individual, community, and county characteristics. American Journal of Criminal Justice, 37(2), 229–245. https://doi.org/10.1007/s12103-011-9125-3.
Putrik, P. (2019). Assessing the role of criminality in neighbourhood safety feelings and self-reported health: Results from a cross-sectional study in a Dutch municipality. BMC Public Health, 19(1), 920. https://doi.org/10.1186/s12889-019-7197-z.
Reid, I. D. (2020). Developing a model of perceptions of security and insecurity in the context of crime. Psychiatry, Psychology and Law, 27(4), 620–636. https://doi.org/10.1080/13218719.2020.1742235.
Ross, C. E., & Jang, S. J. (2000). Neighborhood disorder, fear, and mistrust: The buffering role of social ties with neighbors. American Journal of Community Psychology, 28(4), 401–420. https://doi.org/10.1023/A:1005137713332.
Rountree, P. W., & Land, K. C. (1996). Burglary victimization, perceptions of crime risk, and routine activities: A multilevel analysis across Seattle neighborhoods and census tracts. Journal of Research in Crime and Delinquency, 33(2), 147–180. https://doi.org/10.1177/0022427896033002001.
Sampson, R. J. (1987). Urban black violence: The effect of male joblessness and family disruption. American Journal of Sociology, 93(2), 348–382.
Sari, E. D. K., & Mahmudi, I. (2024). Analisis pemodelan Rasch pada assessment pendidikan (analisis dengan menggunakan aplikasi Winstep). PT. Pena Persada Kerta Utama.
Scottish Government. (2023a). Repeat violence in Scotland: A qualitative approach. http://www.gov.scot/publications/repeat-violence-scotland-qualitative-approach/
Scottish Government. (2023b). Scottish crime and justice survey 2021/22. http://www.gov.scot/news/scottish-crime-justice-survey/
Setiawan, I., Dede, M., Sugandi, D., & Widiawaty, M. A. (2019). Investigating urban crime pattern and accessibility using geographic information system in Bandung City. KnE Social Sciences, 3, 535–548. https://doi.org/10.18502/kss.v3i21.4993
Solari, C. D. (2012). Affluent nighborhood persistence and change in U.S. cities. City & Community, 11(4), 370–388. https://doi.org/10.1111/j.1540-6040.2012.01422.x
Sumintono, B., & Widhiarso, W. (2014). Aplikasi model Rasch untuk penelitian ilmu-ilmu sosial. Trim Komunikata Publishing House.
Susiati, H., Widiawaty, M. A., Dede, M., Akbar, A. A., & Udiyani, P. M. (2022). Modeling of shoreline changes in West Kalimantan using remote sensing and historical maps. International Journal of Conservation Science, 13(3), 1043–1056. https://doi.org/10.5281/zenodo.7109747
Velasquez, A. J. (2021). What predicts how safe people feel in their neighborhoods and does it depend on functional status? SSM - Population Health, 16, 100927. https://doi.org/10.1016/j.ssmph.2021.100927.
Yudiana, W., Susanto, H., & Triwahyuni, A. (2019). Undergraduate students’ intelligence profiles according to the Tes Intelligensi Kolektif Indonesia Tinggi (TIKI-T): A cluster analysis based on the Rasch Model Person ability. Makara Human Behavior Studies in Asia, 23(1), 84–96. https://doi.org/10.7454/hubs.asia.1180718.
Yulia, M., & Suhandy, D. (2014). Seleksi panjang gelombang yang efisien pada NIR spectroscopy untuk pengukuran kandungan padatan terlarut buah salak pondoh menggunakan model forward interval PLS (FiPLS). In Efficient Wavelength Selection in Nir Spectroscopy for Measuring the Dissolved Solids Content of Pondoh Salak Fruit Using the Forward Interval PLS (FiPLS: Vol. Model]’, 6.
Yusep, S. (2009). Perlukah cross validation dilakukan? Perbandingan antara mean square prediction error dan mean square error sebagai penaksir harapan kuadrat kekeliruan model. Seminar Nasional Matematika dan Pendidikan Matematika. http://www.uny.ac.id
Zuberi, A. (2018). Feeling safe in a dangerous place: Exploring the neighborhood safety perceptions of low-income African American youth. Journal of Adolescent Research, 33(1), 90–116. https://doi.org/10.1177/0743558416684948.
DOI: https://doi.org/10.37905/jgej.v6i2.32405
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