IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-04021-1.html
   My bibliography  Save this article

Violence against women and girls in Dorset, United Kingdom: an epidemiological study of perpetrators and locations based on police records

Author

Listed:
  • Jessica Pearcey

    (University of Cambridge)

  • Barak Ariel

    (University of Cambridge
    Hebrew University, Mount Scopus)

  • Vincent Harinam

    (Mournival Applied Research)

  • Noy Assaraf

    (Hebrew University, Mount Scopus)

Abstract

Violence against women and girls (VAWG) continues to be a prevalent phenomenon, yet where it is more likely to occur in the public domain and how offenders assault victims remain understudied areas of interest. This analysis is based on police records on VAWG from Dorset, United Kingdom (UK), using descriptive and spatial statistical methods alongside k-means longitudinal clustering. The spatial analysis uses hexagonal tessellations with a maximum area of 100 m² to identify VAWG hotspots. Findings reveal a significant concentration of public-place VAWG harm in a few spots: half of the reported VAWG occurred within just 2.6% of these hexagons. The study also illustrates a consistent trend in VAWG occurrences, with areas categorised as low, moderate, and high in VAWG counts and measured harm remaining constant over time. However, offenders responsible for the majority of counts and harm are not predominantly active in the hotspots with the highest counts and harm, which suggests a stochastic modus operandi rather than a fixation on specific locations. The identified VAWG hotspots and patterns in offender behaviour provide valuable insights for implementing targeted crime management strategies, and underscore the need to integrate factors like frequency, recentness, degree of harm, and geographical location to assess and address VAWG risks effectively.

Suggested Citation

  • Jessica Pearcey & Barak Ariel & Vincent Harinam & Noy Assaraf, 2024. "Violence against women and girls in Dorset, United Kingdom: an epidemiological study of perpetrators and locations based on police records," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-04021-1
    DOI: 10.1057/s41599-024-04021-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-04021-1
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-024-04021-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Birch, Colin P.D. & Oom, Sander P. & Beecham, Jonathan A., 2007. "Rectangular and hexagonal grids used for observation, experiment and simulation in ecology," Ecological Modelling, Elsevier, vol. 206(3), pages 347-359.
    2. Christophe Genolini & Bruno Falissard, 2010. "KmL: k-means for longitudinal data," Computational Statistics, Springer, vol. 25(2), pages 317-328, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. I. Albarrán & P. Alonso-González & J. M. Marin, 2017. "Some criticism to a general model in Solvency II: an explanation from a clustering point of view," Empirical Economics, Springer, vol. 52(4), pages 1289-1308, June.
    2. Sungsoo Yoon & Youngjoo Moon & Jinah Jeong & Chan-Ryul Park & Wanmo Kang, 2021. "A Network-Based Approach for Reducing Pedestrian Exposure to PM 2.5 Induced by Road Traffic in Seoul," Land, MDPI, vol. 10(10), pages 1-14, October.
    3. Christopher T. Emrich & Yao Zhou & Sanam K. Aksha & Herbert E. Longenecker, 2022. "Creating a Nationwide Composite Hazard Index Using Empirically Based Threat Assessment Approaches Applied to Open Geospatial Data," Sustainability, MDPI, vol. 14(5), pages 1-25, February.
    4. Boura, Georgia & Ferguson, Neil S., 2024. "Incorporating geographic interdependencies into the resilience assessment of multimodal public transport networks," Journal of Transport Geography, Elsevier, vol. 118(C).
    5. Maria Fabrizia Clemente, 2022. "The Future Impacts of ESL Events in Euro-Mediterranean Coastal Cities: The Coast-RiskBySea Model to Assess the Potential Economic Damages in Naples, Marseille and Barcelona," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
    6. Ryzhkov, Alexander & Sarzhan, Yuliya, 2020. "Market initiative and central planning: A study of the Moscow bus network," Research in Transportation Economics, Elsevier, vol. 83(C).
    7. Marchetti, Yuliya & Nguyen, Hai & Braverman, Amy & Cressie, Noel, 2018. "Spatial data compression via adaptive dispersion clustering," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 138-153.
    8. Qiyao Han & Greg Keeffe, 2019. "Mapping the Flow of Forest Migration through the City under Climate Change," Urban Planning, Cogitatio Press, vol. 4(1), pages 139-151.
    9. İ. Esra Büyüktahtakın & Robert G. Haight, 2018. "A review of operations research models in invasive species management: state of the art, challenges, and future directions," Annals of Operations Research, Springer, vol. 271(2), pages 357-403, December.
    10. Nogueira Terra, Talita & Ferreira dos Santos, Rozely, 2012. "Measuring cumulative effects in a fragmented landscape," Ecological Modelling, Elsevier, vol. 228(C), pages 89-95.
    11. Alonso, Pablo J., 2011. "Why using a general model in Solvency II is not a good idea : an explanation from a Bayesian point of view," DES - Working Papers. Statistics and Econometrics. WS ws113729, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Jean-Baptiste Pingault & Sylvana M Côté & Eric Lacourse & Cédric Galéra & Frank Vitaro & Richard E Tremblay, 2013. "Childhood Hyperactivity, Physical Aggression and Criminality: A 19-Year Prospective Population-Based Study," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-7, May.
    13. Burdziej Jan, 2019. "Using hexagonal grids and network analysis for spatial accessibility assessment in urban environments – a case study of public amenities in Toruń," Miscellanea Geographica. Regional Studies on Development, Sciendo, vol. 23(2), pages 99-110, June.
    14. Pasquale De Toro & Enrico Formato & Nicola Fierro, 2023. "Sustainability Assessments of Peri-Urban Areas: An Evaluation Model for the Territorialization of the Sustainable Development Goals," Land, MDPI, vol. 12(7), pages 1-32, July.
    15. Kıbış, Eyyüb Y. & Büyüktahtakın, İ. Esra, 2017. "Optimizing invasive species management: A mixed-integer linear programming approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 308-321.
    16. Pereira, Rafael H.M., 2019. "Future accessibility impacts of transport policy scenarios: Equity and sensitivity to travel time thresholds for Bus Rapid Transit expansion in Rio de Janeiro," Journal of Transport Geography, Elsevier, vol. 74(C), pages 321-332.
    17. Kunegel-Lion, Mélodie & Neilson, Eric W. & Mansuy, Nicolas & Goodsman, Devin W., 2022. "Habitat quality does not predict animal population abundance on frequently disturbed landscapes," Ecological Modelling, Elsevier, vol. 469(C).
    18. Wallentin, Gudrun, 2017. "Spatial simulation: A spatial perspective on individual-based ecology—a review," Ecological Modelling, Elsevier, vol. 350(C), pages 30-41.
    19. Conner, Mary M. & Ebinger, Michael R. & Knowlton, Frederick F., 2008. "Evaluating coyote management strategies using a spatially explicit, individual-based, socially structured population model," Ecological Modelling, Elsevier, vol. 219(1), pages 234-247.
    20. Satoshi Usami & Ross Jacobucci & Timothy Hayes, 2019. "The performance of latent growth curve model-based structural equation model trees to uncover population heterogeneity in growth trajectories," Computational Statistics, Springer, vol. 34(1), pages 1-22, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-04021-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.