Inequality, Deprivation, Punishment and Crime: Theoretical and Experimental Investigations

Gastvortrag

  • Datum: 14.06.2021
  • Uhrzeit: 16:00
  • Vortragender: Prof. Daniel Nettle (Professor of Behavioural Science at Newcastle University)
  • Ort: per Zoom | Gäste sind herzlich eingeladen!
  • Gastgeber: Max-Planck-Institut zur Erforschung von Kriminalität, Sicherheit und Recht
  • Kontakt: c.hillemanns@csl.mpg.de
Inequality, Deprivation, Punishment and Crime: Theoretical and Experimental Investigations
Grea­ter so­cioe­co­no­mic in­e­qua­li­ty is as­so­cia­ted with hig­her cri­me ra­tes. If this as­so­cia­ti­on is cau­sal, it is un­cle­ar how the po­pu­la­tion-le­vel va­ria­ble, in­e­qua­li­ty, af­fects de­ci­si­ons to of­fend in in­di­vi­du­als’ heads. I will pre­sent a re­cent theo­re­ti­cal mo­del in which in­di­vi­du­als strive to re­main their re­sources abo­ve a thres­hold of de­spe­ra­ti­on that is set by their so­ci­al con­text. Grea­ter in­e­qua­li­ty means mo­re in­di­vi­du­als who are at or be­low this thres­hold. It be­co­mes ra­tio­nal for them to of­fend as a ris­ky stra­t­egy to leap cle­ar of it. This pro­du­ces a link bet­ween po­pu­la­ti­on-le­vel in­e­qua­li­ty and in­di­vi­du­al de­ci­si­on-ma­king. Mo­reo­ver, we show that in­cre­a­sing pu­nis­h­ment se­ve­ri­ty un­der the­se as­s­ump­ti­ons should not ge­ne­ral­ly ex­pec­ted to re­du­ce of­fen­ding. I pre­sent a fra­me­work for stu­dy­ing the as­s­ump­ti­ons and pre­dic­ti­ons of the mo­del in a mul­ti-player in­cen­ti­vi­zed eco­no­mic ga­me. Pre­li­mi­na­ry da­ta are con­sis­tent with the pre­dic­ti­ons of the mo­del. Ho­we­ver, they are al­so con­sis­tent with simp­ler but still re­le­vant hy­po­the­ses that do not use the as­s­ump­ti­on of a de­spe­ra­ti­on thres­hold, such as that loss com­pa­red to so­me men­tal re­fe­rence point leads to frus­tra­ti­on and an­ger. We are current­ly at­t­emp­ting to test bet­ween the­se al­ter­na­ti­ves. We ho­pe that the ex­pe­ri­men­tal fra­me­work, re­gard­less of which way the re­sults fall out, is use­ful for un­der­stan­ding an­ti­so­ci­al mo­ti­va­ti­ons.


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