scholarly journals Life-Course Criminal Trajectories of Mafia Members

2019 ◽  
Vol 67 (1) ◽  
pp. 111-141 ◽  
Author(s):  
Gian Maria Campedelli ◽  
Francesco Calderoni ◽  
Tommaso Comunale ◽  
Cecilia Meneghini
Keyword(s):  
Life Course ◽  
High Frequency ◽  
Turning Point ◽  
Low Frequency ◽  
Criminal Careers ◽  
Criminal Career ◽  
Criminal Records ◽  
Data Set ◽  
Career Criminals ◽  
Early Starter

Through a novel data set comprising the criminal records of 11,138 convicted mafia offenders, we compute criminal career parameters and trajectories through group-based trajectory modeling. Mafia offenders report prolific and persistent careers (16.1 crimes over 16.5 years on average), with five distinct trajectories (low frequency, high frequency, early starter, moderate persistence, high persistence). While showing some similarities with general offenders, the trajectories of mafia offenders also exhibit significant differences, with several groups offending well into their middle and late adulthood, notwithstanding intense criminal justice sanctions. These patterns suggest that several mafia offenders are life-course persisters and career criminals and that the involvement in the mafias is a negative turning point extending the criminal careers beyond those observed in general offenders.

scholarly journals Risk Factors of Early Adolescence in the Criminal Career of Polish Offenders in the Light of Life Course Theory

2021 ◽  
Vol 18 (12) ◽  
pp. 6583
Author(s):  
Krzysztof Pękala ◽  
Andrzej Kacprzak ◽  
Anna Pękala-Wojciechowska ◽  
Piotr Chomczyński ◽  
Michał Olszewski ◽  
...  
Keyword(s):  
Juvenile Offenders ◽  
Life Course ◽  
Empirical Studies ◽  
Criminal Careers ◽  
Criminal Career ◽  
Life Course Theory ◽  
Criminal Records ◽  
Age Related ◽  
Work Family ◽  
Depth Interviews

Life course theory (LCT) diagnoses childhood and adolescent factors that determine an individual’s involvement in crime in the future. Farrington lists eight key correlates identified by empirical analyses of criminal careers. In this paper, we seek to discuss the inconsistencies with LCT that we observed in our three empirical studies of the criminal careers of Polish offenders. During 12 years of qualitative research, we conducted direct observations and in-depth interviews in juvenile correction institutions (21) and prisons (8) across the country. We gained access to incarcerated (102) and released (30) juvenile offenders, as well as to incarcerated (68) and released (28) adult offenders. We also conducted in-depth interviews (92) with experts working with young and adult offenders. We similarly accessed some offenders’ criminal records and psychological opinions. Our study revealed the strong presence of family and neighborhood influences on early criminality. Contrary to LCT assumptions, state-dependent institutions (military, work, family) were not strong enough determinants of delinquency. Polish offenders generally experience criminal onset later than LCT-oriented criminologists indicate. Based on our data, we also agree with the thesis that the onset of crime should be discussed as different age-related periods rather than just a general onset.

Jekyll or Hyde? Examining the criminal careers of public violence offenders

2016 ◽  
Vol 14 (4) ◽  
pp. 415-433 ◽  
Author(s):  
Tom van Ham ◽  
Arjan A.J. Blokland ◽  
Henk B. Ferwerda ◽  
Theo A.H. Doreleijers ◽  
Otto M.J. Adang
Keyword(s):  
Small Group ◽  
Empirical Work ◽  
Criminal Careers ◽  
Criminal Career ◽  
Future Research ◽  
Intergroup Dynamics ◽  
Criminal Records ◽  
Career Trajectories ◽  
Police Data ◽  
Group Violence

Since the 1970s theoretical and empirical work on public violence has mainly focused on the context in which public violence takes place, assuming that public violence offenders are ordinary people acting in extraordinary circumstances. Recent studies however indicate that ‘hooligans’ share many characteristics with other violent offenders, which has (re)fuelled the notion that individual propensity is important in explaining public violence, and that public violence offenders generally fit the small group of serious and persistent offenders identified by Moffitt. Based on Dutch police data on 438 individuals involved in public violence, we examined the criminal careers of public violence offenders leading up to the date of registration as a public violence offender. Using group-based models, we distinguished three criminal career trajectories in our sample. Although we found many public violence offenders had no criminal records whatsoever, we also found a small group of public violence offenders who exhibited a high frequency of offending, displayed both solo and group violence, and acted violently across different settings. Our results leave us to take a middle ground in the context-propensity debate, because we argue that different categories of public violence offenders may exist whose behaviour is triggered by different processes. Incorporating the notion of different types of public violence offenders helps explain the seemingly contradictory findings of prior studies, and suggests new avenues for future research into the intra- and intergroup dynamics of public violence.

scholarly journals Postoperative seizure outcome-guided machine learning for interictal electrocorticography in neocortical epilepsy

2018 ◽  
Vol 119 (6) ◽  
pp. 2265-2275 ◽  
Author(s):  
Seong-Cheol Park ◽  
Chun Kee Chung
Keyword(s):  
Machine Learning ◽  
Free Group ◽  
High Frequency ◽  
Low Frequency ◽  
Outcome Data ◽  
Training Data ◽  
Seizure Outcome ◽  
Data Set ◽  
Neocortical Epilepsy ◽  
Postoperative Seizure

The objective of this study was to introduce a new machine learning guided by outcome of resective epilepsy surgery defined as the presence/absence of seizures to improve data mining for interictal pathological activities in neocortical epilepsy. Electrocorticographies for 39 patients with medically intractable neocortical epilepsy were analyzed. We separately analyzed 38 frequencies from 0.9 to 800 Hz including both high-frequency activities and low-frequency activities to select bands related to seizure outcome. An automatic detector using amplitude-duration-number thresholds was used. Interictal electrocorticography data sets of 8 min for each patient were selected. In the first training data set of 20 patients, the automatic detector was optimized to best differentiate the seizure-free group from not-seizure-free-group based on ranks of resection percentages of activities detected using a genetic algorithm. The optimization was validated in a different data set of 19 patients. There were 16 (41%) seizure-free patients. The mean follow-up duration was 21 ± 11 mo (range, 13–44 mo). After validation, frequencies significantly related to seizure outcome were 5.8, 8.4–25, 30, 36, 52, and 75 among low-frequency activities and 108 and 800 Hz among high-frequency activities. Resection for 5.8, 8.4–25, 108, and 800 Hz activities consistently improved seizure outcome. Resection effects of 17–36, 52, and 75 Hz activities on seizure outcome were variable according to thresholds. We developed and validated an automated detector for monitoring interictal pathological and inhibitory/physiological activities in neocortical epilepsy using a data-driven approach through outcome-guided machine learning. NEW & NOTEWORTHY Outcome-guided machine learning based on seizure outcome was used to improve detections for interictal electrocorticographic low- and high-frequency activities. This method resulted in better separation of seizure outcome groups than others reported in the literature. The automatic detector can be trained without human intervention and no prior information. It is based only on objective seizure outcome data without relying on an expert’s manual annotations. Using the method, we could find and characterize pathological and inhibitory activities.

Co-offending

2018 ◽  
pp. 125-146
Author(s):  
Sarah B. van Mastrigt ◽  
Peter Carrington
Keyword(s):  
Life Course ◽  
Empirical Evidence ◽  
Criminal Careers ◽  
Criminal Career ◽  
Future Research ◽  
Offending Patterns ◽  
The Life Course

This chapter reviews existing theory and empirical evidence on changes in co-offending patterns over the life course, links these patterns to other key criminal career parameters, and highlights important areas for future research. In order to set the stage for the remainder of the chapter, the few theoretical insights that relate joint offending to the development of criminal careers are first reviewed. The chapter then focuses on the age–co-offending curve, outlining what is known about changes in both co-offending prevalence and form across the life course and considering implications for more general developmental and life-course discussions of age and offending. It next examines how co-offending is related to other features of the criminal career, including onset, specialization, seriousness, frequency, duration, persistence, and desistance. Finally, this chapter briefly outlines outstanding issues and next steps for advancing DLC theory and research on group crime.

The criminal career trajectories of domestic violence offenders

2021 ◽  
Author(s):  
Christopher Dowling ◽  
Hayley Boxall
Keyword(s):  
Domestic Violence ◽  
New South ◽  
Low Frequency ◽  
Criminal Careers ◽  
Criminal Career ◽  
Career Trajectories ◽  
South Wales ◽  
Formed Part ◽  
Underlying Risk ◽  
Trajectory Modelling

This study examines the officially recorded criminal careers of 2,076 domestic violence offenders and 9,925 non-domestic violence offenders in New South Wales in the 10 years following their first police proceeding. Group-based trajectory modelling was used to examine both domestic violence and non-domestic violence offending. Special attention is given to the degree of versatility in offending, and to the interplay of domestic violence and non-domestic violence offending trajectories. Domestic violence offending often formed part of a broader pattern of offending. While trajectories of low‑frequency domestic violence and non-domestic violence offending were most common, domestic violence typically increases as non-domestic violence offences begin to decline. Importantly, there was variability in the offending profiles of domestic violence offenders. This was amplified when non-domestic violence offending was analysed, indicative of a complex array of underlying risk factors.

A teleseism-specific detection algorithm for single short-period traces

1983 ◽  
Vol 73 (4) ◽  
pp. 1173-1186
Author(s):  
John R. Evans ◽  
Stephen S. Allen
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Vertical Component ◽  
Low Frequency ◽  
Field Studies ◽  
Detection Algorithm ◽  
P Waves ◽  
Data Set ◽  
Short Period ◽  
Worldwide Network

abstract An algorithm for microprocessor-controlled seismographic recorders is described which reliably detects major phases from earthquakes more than 3° from the sensor but rejects noise events and most earthquakes closer than 3°. Unusually large earthquakes within 3° also are detected. The algorithm is applicable to field studies using triggered seismographs to record teleseismic P waves, to worldwide network automation, and to scanning records for teleseisms. It uses two band-pass filtered data streams evolved from a single short-period vertical-component seismometer to differentiate (low-frequency) teleseisms from other signals; the low-frequency band (0.5 to 2.0 Hz) declares “triggers” while the high-frequency band (3.0 to 8.0 Hz) inhibits any of these triggers generated by broadband signals such as local earthquakes. Locally generated noise is usually high frequency and does not excite the low-frequency band. A 16-bit fixed-word-length implementation of this algorithm detected 82 per cent of good P phases (readable to ±0.25 sec) occurring more than 20° from the seismograph, and 50 per cent of earthquakes between 3° and 20°, in a test data set comprising 23 hr of data in 93 segments. The same implementation of the algorithm rejected most noise and 91 per cent of earthquakes within 3° of the seismograph.

DWT Based Blind Watermark in Relational Database

2013 ◽  
Vol 760-762 ◽  
pp. 2123-2128
Author(s):  
Yi Liu ◽  
Juan Wang
Keyword(s):  
Wavelet Transform ◽  
Theoretical Analysis ◽  
Data Fusion ◽  
Relational Database ◽  
High Frequency ◽  
Low Frequency ◽  
Blind Watermarking ◽  
Watermark Image ◽  
Data Set ◽  
Strong Robustness

Aiming to balance the robustness and imperceptibility of database watermark, propose a wavelet transform (DWT) based blind watermarking algorithm. The algorithm screens candidate attributes that can be embedded watermark and conducts subset segmentation and rearrangement, and then performs DWT transformation to the data subsets and the scrambled watermark image respectively. Embed the compressed low-frequency part of the watermark into the High-frequency part of the data set to achieve data fusion. Theoretical analysis and experiments show that the algorithm enjoys strong robustness and good invisibility.

scholarly journals Testing Two Theories of Criminal Careers: A Criminal Career Profile Approach

2021 ◽  
Author(s):  
◽  
Joanne Clare Cahill
Keyword(s):  
High Risk ◽  
Life Course ◽  
Criminal Careers ◽  
Criminal Career ◽  
Criminal Behaviour ◽  
Limited Evidence ◽  
Social Controls ◽  
Life Course Persistent ◽  
Career Research ◽  
Profile Approach

<p>Criminal career research has emerged as a field interested in determining the factors related to the onset, frequency, duration, maintenance, and desistance of criminal behaviour (Blumstein & Cohen, 1987; Blumstein, Cohen, & Farrington, 1988). Various theories have been developed to account for these components of the criminal career, and the present research aims to examine the desistance components of two such theories in a sample of high risk adult offenders. Looking first at Moffitt’s (1993) adolescencelimited/ life-course persistent perspective, and then at Laub and Sampson’s (1993; Sampson & Laub, 2005) theory of informal social controls, there is limited evidence that either frequency of conviction or criminal career seriousness in high risk adult offenders can be explained well by reference to either of these theories alone. Although components of each theory appear to have some support within this sample, it is important to note that the prediction of future seriousness appears to be particularly difficult. Implications of these findings are discussed, with particular reference to policy concerns and areas for additional research.</p>

scholarly journals Investigation of the Relationship Between the Yucatan Channel Transport and the Loop Current Area in a Multidecadal Numerical Simulation

2014 ◽  
Vol 48 (4) ◽  
pp. 15-26 ◽  
Author(s):  
Robert Nedbor-Gross ◽  
Dmitry S. Dukhovskoy ◽  
Mark A. Bourassa ◽  
Steven L. Morey ◽  
Eric P. Chassignet
Keyword(s):  
High Frequency ◽  
Time Derivative ◽  
Low Frequency ◽  
Strong Relationship ◽  
Ocean Model ◽  
Rate Of Change ◽  
Loop Current ◽  
Data Set ◽  
Florida Straits ◽  
Yucatan Channel

Abstract A hypothesis by Maul (1977), stating the rate of change of loop current (LC) volume is related to deep Yucatan Channel (YC) transport, is tested with a continuous 54-year simulation of the Gulf of Mexico (GoM) using a regional 1/25° resolution Hybrid Coordinate Ocean Model (HYCOM) configuration. The hypothesis states that the imbalance of transport between the upper YC and the Florida Straits controls the rate of change of the LC volume and that the imbalance is compensated by transport through the deep YC. Bunge et al. (2002) found a strong relationship between the deep YC transport and the LC area using 7.5 months of data from a mooring array in the YC, but the observational record length was relatively short compared to the time scale of LC variability. The 54-year HYCOM simulation provides a much longer and spatially complete data set to study the LC variability. Results show that the time evolution of the LC between two shedding events can be viewed as a combination of relatively high-frequency fluctuations superimposed on a low-frequency trend. The high-frequency variability of the LC area time derivative and the deep YC transport are related. The low-frequency variability is examined by comparing the LC area time series with time-integrated transport in the deep YC, and statistically similar trends are identified, supporting the Maul (1977) theory.

Acceleration, Deceleration, Escalation, and De-escalation

2018 ◽  
pp. 69-80
Author(s):  
Wesley G. Jennings ◽  
Bryanna Hahn Fox
Keyword(s):  
Life Course ◽  
Criminal Careers ◽  
Criminal Career ◽  
Future Research

This chapter examines two patterns of change seen in individual offending behaviors at certain times and ages: acceleration or deceleration and escalation or de-escalation. In order to answer the questions regarding the age–crime curve and its applicability to the criminal careers of specific individuals, the prevalence of offending in the population and the frequency of offending within individual criminal careers must be examined through these patterns. Hence, the chapter begins with a brief review of the origin of the criminal career paradigm and a description of its various parameters. It then discusses both static and dynamic developmental and life-course theories of crime before providing a more in-depth discussion of acceleration/deceleration and escalation/de-escalation as it relates to a criminal career, respectively. Finally, this chapter concludes by offering directions for future research on these topics.

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