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UID:pretalx-2026-H9JTTM@conferences.acspri.org.au
DTSTART;TZID=AEST:20261126T144500
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DESCRIPTION:Recently\, there has been growing concern about youth crime and
  its impact\, both in Australia and internationally. Across Australian jur
 isdictions there has been an observed incline in violent and serious offen
 ces committed by young people (e.g.\, Armytage\, 2017\; Australian Bureau 
 of Statistics\, 2024). Despite this\, the key drivers behind these changes
  in youth offending patterns remain poorly understood. Increasingly\, yout
 h crime is being characterised as a network phenomenon (Shepherd & Spivak\
 , 2020)\, with co-offending emerging as a potential driver in changes in v
 iolent offending patterns. Research on co-offending and group-based violen
 ce has grown considerably\, yet little is known about how social embeddedn
 ess\, the extent to which individuals are situated within co-offending net
 works shapes the formation of violent incidents. \n\nThis study examined y
 outh co-offending from a two-mode (actor-event) network approach\, examini
 ng structural embeddedness (position within the network) as a key dimensio
 n of social embeddedness. Using relational hyperevent models\, observed vi
 olent co-offending groups were compared against size-matched counterfactua
 l groups drawn from ten years (2015–2024) of administrative police recor
 ds for young people in two urban Queensland districts. RHEM are well suite
 d to analysing multi-actor events such as co-offending because they preser
 ve the structure of co-offending groups\, including group size\, event tim
 ing\, and actor interdependencies. Importantly\, this avoids information l
 oss that occurs in traditional social network analyses\, which typically t
 reat multi-actor events as a collection of separate dyads (Lerner et al.\,
  2019). \n\n\nFindings revealed that structural embeddedness significantly
  predicted the formation of violent co-offending events\, with violence co
 ncentrating among connected youth and among groups of structurally similar
  peers. The findings will help inform and strengthen criminal justice resp
 onses to youth co-offending by identifying key network factors that contri
 bute to violent offending patterns. Expanding the knowledge base on co-off
 ending can help inform strategies to disrupt the formation of antisocial g
 roups and networks\, to divert individuals away from crime\, and to reduce
  the likelihood of young people becoming embedded in co-offending groups\,
  and progressing to adult or persistent violent offending. \n\nReferences\
 nArmytage\, P. (2017). Youth Justice Review and Strategy: Meeting needs an
 d reducing offending. Department of Justice and Community Safety. https://
 apo.org.au/node/101051\nAustralian Bureau of Statistics. (2024). Recorded 
 Crime—Offenders: Statistics about offenders proceeded against by police\
 , including demographic\, most serious offence\, and family and domestic v
 iolence information. https://www.abs.gov.au/statistics/people/crime-and-ju
 stice/recorded-crime-offenders/latest-release#key-statistics \nLerner\, J.
 \, Tranmer\, M.\, Mowbray\, J.\, & Hancean\, M. G. (2019). REM beyond dyad
 s: relational hyperevent models for multi-actor interaction networks. http
 s://doi.org/10.48550/arXiv.1912.07403\nShepherd\, S. M.\, & Spivak\, B. L.
  (2020). Estimating the extent and nature of offending by Sudanese-born in
 dividuals in Victoria. Australian & New Zealand Journal of Criminology\, 5
 3(3)\, 352–368.
DTSTAMP:20261102T131211Z
LOCATION:MacCallum Room
SUMMARY:Structural Embeddedness and Violent Youth Co-offending: Applying a 
 Relational Hyperevent Model (RHEM) - Shaun McLaws
URL:https://conferences.acspri.org.au/2026/talk/H9JTTM/
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