|
|
|
|
| LEADER |
00000caa a22000002c 4500 |
| 001 |
1588524566 |
| 003 |
DE-627 |
| 005 |
20241119230906.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
190219s2013 xx |||||o 00| ||eng c |
| 024 |
7 |
|
|a 10.1186/2190-8532-2-4
|2 doi
|
| 035 |
|
|
|a (DE-627)1588524566
|
| 035 |
|
|
|a (DE-576)518524566
|
| 035 |
|
|
|a (DE-599)BSZ518524566
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 082 |
0 |
4 |
|a 340
|a 301
|
| 084 |
|
|
|a 2,1
|2 ssgn
|
| 100 |
1 |
|
|8 1\p
|a Masías Hinojosa, Víctor Hugo
|d 1979-
|0 (DE-588)1232037745
|0 (DE-627)1755757972
|4 aut
|
| 109 |
|
|
|a Masías Hinojosa, Víctor Hugo 1979-
|a Masías, Víctor Hugo 1979-
|a Masías, Víctor H. 1979-
|a Hugo Masías Hinojos, Víctor 1979-
|a Hinojos, Víctor Hugo Masía 1979-
|a Masías H., V. H. 1979-
|a Masías-H., Víctor-H. 1979-
|
| 245 |
1 |
0 |
|a Predicting sentencing outcomes with centrality measures
|
| 264 |
|
1 |
|c 2013
|
| 336 |
|
|
|a Text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a Computermedien
|b c
|2 rdamedia
|
| 338 |
|
|
|a Online-Ressource
|b cr
|2 rdacarrier
|
| 520 |
|
|
|a Despite their importance for stakeholders in the criminal justice system, few methods have been developed for determining which criminal behavior variables will produce accurate sentence predictions. Some approaches found in the literature resort to techniques based on indirect variables, but not on the social network behavior with exception of the work of Baker and Faulkner [ASR 58: 837–860, 1993]. Using information on the Caviar Network narcotics trafficking group as a real-world case, we attempt to explain sentencing outcomes employing the social network indicators. Specifically, we report the ability of centrality measures to predict a) the verdict (innocent or guilty) and b) the sentence length in years. We show that while the set of indicators described by Baker and Faulkner yields good predictions, introduction of the additional centrality measures generates better predictions. Some ideas for orienting future research on further improvements to sentencing outcome prediction
|
| 650 |
|
4 |
|a Kriminologie
|
| 650 |
|
4 |
|a Drogenkriminalität
|
| 650 |
|
4 |
|a Soziales Netzwerk
|
| 650 |
|
4 |
|a Strafverfolgung
|
| 650 |
|
4 |
|a Justiz
|
| 650 |
|
4 |
|a Netzwerkanalyse
|
| 650 |
|
4 |
|a Criminology
|
| 650 |
|
4 |
|a Sentencing outcomes
|
| 650 |
|
4 |
|a Social Networks
|
| 700 |
1 |
|
|a Morselli, Carlo
|4 oth
|
| 700 |
1 |
|
|a Crespo, Fernando
|4 oth
|
| 700 |
1 |
|
|a Laengle, Sigifredo
|4 oth
|
| 773 |
0 |
8 |
|i In
|a Security Informatics
|g 2(2013), 4, Seite 1-9
|
| 773 |
1 |
8 |
|g volume:2
|g year:2013
|g number:4
|g pages:1-9
|
| 856 |
|
|
|u https://security-informatics.springeropen.com/counter/pdf/10.1186/2190-8532-2-4
|x unpaywall
|z Vermutlich kostenfreier Zugang
|h publisher [open (via page says license)]
|
| 856 |
4 |
0 |
|u https://doi.org/10.1186/2190-8532-2-4
|x Resolving-System
|z kostenfrei
|3 Volltext
|
| 883 |
|
|
|8 1
|a cgwrk
|d 20241001
|q DE-101
|u https://d-nb.info/provenance/plan#cgwrk
|
| 935 |
|
|
|a mkri
|
| 951 |
|
|
|a AR
|
| ELC |
|
|
|a 1
|
| LOK |
|
|
|0 000 xxxxxcx a22 zn 4500
|
| LOK |
|
|
|0 001 3057960316
|
| LOK |
|
|
|0 003 DE-627
|
| LOK |
|
|
|0 004 1588524566
|
| LOK |
|
|
|0 005 20190326135028
|
| LOK |
|
|
|0 008 190219||||||||||||||||ger|||||||
|
| LOK |
|
|
|0 035
|a (DE-2619)col_collection_102140000000400
|
| LOK |
|
|
|0 040
|a DE-2619
|c DE-627
|d DE-2619
|
| LOK |
|
|
|0 092
|o n
|
| LOK |
|
|
|0 852
|a DE-2619
|
| LOK |
|
|
|0 852 1
|9 00
|
| LOK |
|
|
|0 935
|a soar
|
| LOK |
|
|
|0 938
|l In: Security Informatics ; 2 (2013)
|8 0
|
| LOK |
|
|
|0 938
|l oai:gesis.izsoz.de:document/36854
|8 1
|
| OAS |
|
|
|a 1
|
| ORI |
|
|
|a SA-MARC-krimdoka001.raw
|
