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\n\nThe project work was funded by the European Commission (EC) 7th Framework Programme (FP7), under the 9th Call for projects on Information and Communication Technologies. The publishing of this book was funded by the EC FP7 Post-Grant Open Access Pilot programme. 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Nguyen received his M.A. in Mathematics, and his Ph.D. in Applied Mathematics from the Claremont Graduate University; M.S.E.E. in Communication Systems Theory from University of California San Diego; and B.S.E. in Electronics and M.S.E. in Electromagnetic Field Theory from California State University Fullerton (CSUF). He also completed all course requirements and passed the comprehensive exam for his M.S.E.E. in Digital Signal Processing from California State University Long Beach. Dr. Nguyen is an expert in Satellite Operations (SATOPS), Satellite Communications (SATCOMs), advanced mathematical modeling for complex systems-of-systems, sensing and communication networks.\nCurrently, he serves as Adjunct Research Professor at CSUF, Mathematics Dept. Concurrently, he is also with the Aerospace Corporation, serving as a Deputy Chief System Architect in Space Systems Architect, Global Partnerships Subdivision. He has more than 13-years of service at Aerospace, and prior to his current position; he has served as Sr. Engineering Specialist, Sr. Project Lead, Section Manager, Associate Director, Interim Director, and Principal Technical Staff (the highest technical level at the corporation). At Aerospace, he invented HPA linearizer, GMSK synchronizers and developed advanced optimization techniques using game theory for achieving affordable and low-risk acquisition strategy. Prior to CSUF, he had also held a Research Assistant Professor at the Catholic University of America in concurrent with The Aerospace Corporation positions. \nHe was a Engineering Fellow from Raytheon, where he had 10-year of services at Raytheon, serving as Program Area Chief Engineer, Program Chief Engineer, PI, Technical Director, Program Manager, Lead Architect and Lead System Engineer for many advanced programs and pursuits related to sensing and communication networks. At Raytheon, he invented radar-communication technology and gun barrel detector using millimeter-wave. Previous to Raytheon and Aerospace Corporation, Dr. Nguyen was with NASA/JPL for more than 11-years, where he served as the NASA delegate to the international Consultative Committee for Space Data System (CCSDS). Many of his works on RF and Modulation were adopted as the CCSDS standards for USB waveforms and space RF systems. At JPL he invented QPSK phase ambiguity resolver and developed innovative optimization technique for simultaneous range-command-telemetry operation. He built the first laser lab and automated manufacturing lab when he was with ITT Technical Services in the early ’80s. \nHe has published more than 250 technical reports and papers. His work has appeared in NASA TechBrief, textbook, Open Access Book, SIAM Publication, CCSDS Blue Book, and Wiley & Sons Encyclopedia of Electrical and Electronics Engineering. He was selected as a Vietnamese-American Role Model by KCSI-TV, Channel 18 in 2002, and Recognition Honoree at 50-Year Celebration of CSUF in 2007. He received numerous Raytheon, Aerospace and NASA awards, and Air Force commendations. He holds 16 patents and has 01 patent pending. His biography has been listed in Marquis Who’sWho in Science and Engineering in America.",institutionString:"The Aerospace Corporation",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"California State University, Fullerton",institutionURL:null,country:{name:"United States of America"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"11",title:"Engineering",slug:"engineering"}],chapters:[{id:"72485",title:"Satellite Control System: Part I - Architecture and Main Components",slug:"satellite-control-system-part-i-architecture-and-main-components",totalDownloads:157,totalCrossrefCites:0,authors:[null]},{id:"72443",title:"Effective Algorithms for Detection Outliers and Cycle Slip Repair in GNSS Data Measurements",slug:"effective-algorithms-for-detection-outliers-and-cycle-slip-repair-in-gnss-data-measurements",totalDownloads:71,totalCrossrefCites:0,authors:[null]},{id:"72147",title:"Future Satellite System Architectures and Practical Design Issues: An Overview",slug:"future-satellite-system-architectures-and-practical-design-issues-an-overview",totalDownloads:132,totalCrossrefCites:0,authors:[{id:"210657",title:"Dr.",name:"Tien",surname:"Nguyen",slug:"tien-nguyen",fullName:"Tien Nguyen"}]},{id:"72340",title:"Game Theoretic Training Enabled Deep Learning Solutions for Rapid Discovery of Satellite Behaviors",slug:"game-theoretic-training-enabled-deep-learning-solutions-for-rapid-discovery-of-satellite-behaviors",totalDownloads:101,totalCrossrefCites:0,authors:[null]},{id:"72725",title:"Communication Subsystems for Satellite Design",slug:"communication-subsystems-for-satellite-design",totalDownloads:239,totalCrossrefCites:0,authors:[null]},{id:"72839",title:"Overview of Existing and Future Advanced Satellite Systems",slug:"overview-of-existing-and-future-advanced-satellite-systems",totalDownloads:58,totalCrossrefCites:0,authors:[null]},{id:"72620",title:"Dynamic Link from Liftoff to Final Orbital Insertion for a MEO Space Vehicle",slug:"dynamic-link-from-liftoff-to-final-orbital-insertion-for-a-meo-space-vehicle",totalDownloads:58,totalCrossrefCites:0,authors:[null]},{id:"72311",title:"System Designs of Microsatellites: A Review of Two Schools of Thoughts",slug:"system-designs-of-microsatellites-a-review-of-two-schools-of-thoughts",totalDownloads:154,totalCrossrefCites:0,authors:[null]},{id:"72742",title:"Design of Intelligent and Open Avionics System Onboard",slug:"design-of-intelligent-and-open-avionics-system-onboard",totalDownloads:48,totalCrossrefCites:0,authors:[null]},{id:"74274",title:"Analysis of Spatiotemporal Variability of Surface Temperature of Okhotsk Sea and Adjacent Waters Using Satellite Data",slug:"analysis-of-spatiotemporal-variability-of-surface-temperature-of-okhotsk-sea-and-adjacent-waters-usi",totalDownloads:35,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"205697",firstName:"Kristina",lastName:"Kardum Cvitan",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/205697/images/5186_n.jpg",email:"kristina.k@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3621",title:"Silver Nanoparticles",subtitle:null,isOpenForSubmission:!1,hash:null,slug:"silver-nanoparticles",bookSignature:"David Pozo Perez",coverURL:"https://cdn.intechopen.com/books/images_new/3621.jpg",editedByType:"Edited by",editors:[{id:"6667",title:"Dr.",name:"David",surname:"Pozo",slug:"david-pozo",fullName:"David Pozo"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"51575",title:"Investigations of Phonons in Zinc Blende and Wurtzite by Raman Spectroscopy",doi:"10.5772/64194",slug:"investigations-of-phonons-in-zinc-blende-and-wurtzite-by-raman-spectroscopy",body:'\nCrystals with cubic/hexagonal structure are of major importance in the fields of electronics and optoelectronics. Zinc blende is typical face‐centered cubic structure, such as Si, Ge, GaAs, and ZnSe. Wurtzite is typical hexagonal close packed structure, such as GaN and ZnSe. In particular, II–VI or III–V group semiconductor nanowires always coexist two structures, one cubic form with zinc blend (ZB) and another hexagonal form with wurtzite (WZ) structure. Sometimes, this coexistence between zinc blende and wurtzite structure leads to form twinning crystal during the phase transformation between zinc blende and wurtzite [1, 2].
\nThe crystal structure of zinc selenide in the zinc blende structures is shown in Figure 1, which is regarded as two face‐centered cubic (fcc) lattices displaced relative to each other by a vector
Zinc blende crystal structure.
Figure 2 is wurtzite structure of zinc selenium. Close‐packed planes of wurtzite are {0001} along <0001>, and the stacking is …ABABA…. Adjacent plane spacing is c/2. Wurtzite structures have four atoms per unit cell. In zinc blende, the bonding is tetrahedral. The wurtzite structure may be generated from zinc blende by rotating adjacent tetrahedra about their common bonding axis by an angle of 60° with respect to each other.
Wurtzite crystal structure.
Research into controlling nanowire crystal structure has intensified. Several reports address the diameter dependency of nanowire crystal structure, with smaller diameter nanowires tending toward a WZ phase and larger diameter nanowires tending toward a ZB phase. Allowing for ZnSe, two phases, zinc blende (ZB) and wurtzite (WZ), exist, and the (111) faces of ZB phase are indistinguishable from and match up with the (001) faces of WZ phase, the subtle structural differences of which lead to the attendant small difference in the internal energies (∼5.3 meV/atom for ZnSe). The WZ‐ZB phase transformation is considered to be caused by the crystal plane slip. Take the formation of ZnSe longitudinal twinning nanowires, for example [3]. Structurally, the (001) planes of WZ and the (111) planes of ZB are their corresponding close packing planes. ABAB stacking for WZ and ABCABC stacking for ZB are shown in Figure 3a and b, respectively. It was noteworthy that the arrangement of atoms in A/B packing planes was different in WZ phase. So the phase transition could not be realized until the smaller Zn atoms moved to the interspaces provided by three neighboring bigger Se atoms, within the plane B. In this case, the new layers B\' were obtained, and then, the slip occurs between neighboring planes A and B’ by
Phase transformation between zinc blende and wurtzite. (a) The arrangement of atoms in WZ phase; (b) The arrangement of atoms in ZB phase; (Se is shown with the bigger sphere and Zn is shown in little one.) (c) The stacking sequence schematic model showing the phase transformation process from WZ phase to ZB phase.
Generally, there are three equivalent directions to realized the slip, which are <120>, <
To the simple double lattice, lattice vibration can be described by the one‐dimensional diatomic model. The linear‐chain model of a diatomic crystal is based upon a system of two atoms with masses, m and M, placed along a one‐dimensional chain as depicted in Figure 4. The separation between the atomics is “a”, and the vibration in the vicinity of their equilibrium position is treated as the simple harmonic vibration. The properties of optical phonon can be described based on the macroscopic fields. It is the model based on the Huang and Maxwell equations, which has great utility in describing the phonons in the uniaxial crystals such as wurtzite crystals.
One‐dimensional diatomic linear‐chain model.
Polar semiconductor is the crystal that consists of different ions. In polar semiconductor, the lattice vibration is associated with the electric dipole moment and electric field generation. Assume that the vibration frequency is ω, wave vector is
Solve the simultaneous formula (2‐1) and Maxwell equations can obtain,\n
To longitudinal polarity lattice mode,
To transverse polarity lattice mode,
As was apparent above, polar optical phonon vibrations produce electric fields and electric polarization fields that may be described in terms of Maxwell\'s equations and the driven‐oscillator equations. Assume that the mass of the ions are
where
where
The lattice vibration is associated with the electric dipole moment generation, which can be described as follows,\n
where
Replace the value of
Then, take formula (2‐7) and (2‐9) into (2‐10),\n
where
\nformula (2‐11) and (2‐12) are the Huang equations, which are the basic equations of describing the vibrations of long wave in the polar crystals. From the formula (2‐14) and (2‐16), one can find that,\n
When the system is under the high‐frequency electric field, formula (2‐12) reduces to\n
For
Compute the curl of formula (2‐11) and solve the simultaneous equations of (2‐12) and electrostatic equations
When the system is under the static electric field,
Take formula (2‐21) into (2‐12),\n
Replace the electrostatic equation,\n
And take formula (2‐23) and (2‐20) into (2‐22),\n
Solve the simultaneous equations of (2‐17) and (2‐24) can obtain\n
Solve two simultaneous Maxwell and Huang equations,\n
Assume the solution forms are\n
Take (2‐28) into the Huang and Maxwell equations,\n
To the longitudinal wave,
Take (2‐19) (2‐20) (2‐25) (2‐26) into (2‐31)\n
Equation (2‐23) is the dispersion relations of longitudinal wave, which is commonly called Lyddane‐Sachs‐Teller (LST) relationship. LST relation indicates that the frequency of longitudinal wave is a constant and independent on the wave vector.
\nSimilarly, to the transverse wave,
Replace the values of A, B, C, and D into (2‐33),\n
Equation (2‐34) is the dispersion relations of transverse wave. One can find that the frequency of transverse is dependent on the value of wave vector
One‐dimensional diatomic model can be regarded as the simple double lattice. In the simple linear chain model, it is assumed that only nearest neighbors are coupled, and that the interaction between these atoms is described by Hooke\'s law; the spring constant α is taken to be that of a harmonic oscillator. Thus, the kinematical equations are established,\n
where m and M are the mass of the adjacent atoms
where
Eliminating A1 and A2,\n
The relationship between frequency and wave vector is commonly called dispersion relation [5].
\nIn this section, we discuss the phonon effects in wurtzite structure. The crystalline structure of a wurtzite material is depicted in Figure 2. There are four atoms in the unit cell. Thus, the total number of optical modes in the long‐wavelength limit is nine: three longitudinal optic (LO) and six transverse optic (TO). In these optical modes, there are only three polar optical vibration modes. According to the group theory, the wurtzite crystal structure belongs to the space group
Due to the anisotropy of wurtzite structure, the vibrational frequency of oscillates parallel and perpendicular to the optical axis is denoted by
where
When the wave vector is parallel to the optical axis,
which is the same as formula (3‐1). When the wave vector is perpendicular to the optical axis,
Formula (3‐4) indicates that the extraordinary wave is transverse wave when the wave vector is perpendicular to the optical axis.
\nWhen
and\n
Formula (3‐5) indicates that frequency of ordinary phonon is independent on the wave vector q. Formula (3‐6) indicates that the frequency of extraordinary phonon is dependent on the orientation of the wave vector, but independent on its value.
\nIt is most convenient to divide uniaxial crystals into two categories: (a) the electrostatic forces dominate over the anisotropy of the interatomic forces and (b) the short‐range interatomic forces are much greater than the electrostatic forces. It has been turned out that crystals with the wurtzite symmetry fall into the first category. In this case,
thus,\n
and\n
Raman spectroscopy is a non‐destructive technical tool used to gain information about the phonon behavior of the crystal lattice through the frequency shift of the inelastically scattered light from the near surface of the sample. It is well known that different crystal phases have different vibrational behaviors, so the measured Raman shifts of different phases are mostly unique and can be seen as fingerprints for the respective phases. This provides the possibility of detecting different phases in a sample. It has been developed to be a versatile tool for the characterization of semiconductors leading to detailed information on crystal structure, phonon dispersion, electronic states, composition, strain, and so on of semiconductor nanostructures.
\nIn a zinc blende structure, the space group of the cubic unit cell is F43m(
The wurtzite crystal structure belongs to the space group
In addition to the attached references, this chapter is primarily written on the basis of our research works. Here, we select ZnSe, Ge nanowires and CdSe/Ge‐based nanowire heterostructures, two‐dimensional semiconductors SnS2 and MoS2, and candidate absorber materials of thin‐film solar cells Cu2ZnSnS4. These examples will help us to understand the phonons behaviors in nanostructures.
\n\nIt is well known that ZnSe has two structures: cubic zinc blende (ZB) and hexagonal wurtzite (WZ) due to the difference of the stacking sequence of successive layers, whereas Ge has diamond structure. SnS2 and MoS2 belong to the wide family of compounds with layered structures. SnS2 crystal is isostructural to the hexagonal CdI2‐type structure. MoS2 usually consists of a mixture of two major polytypes of similar structure, 2H (hexagonal) and 3R (rhombohedral), with the former being more abundant. As for quaternary Cu2ZnSnS4 (CZTS), the parent binary II‐VI semiconductors adopt the cubic zinc blende structure, and the ternary I‐III‐VI2 compounds can be generated by mutating the group II atoms into pairs of group I and III atoms. The quaternary CZTS materials are formed by replacing the two In (III) atoms with Zn (II) and Sn (IV), respectively (see Figure 5).
\nEvolution of multinary compounds.
Room temperature Raman spectra of ZnSe. S1, S2, and S3 stand for ZB, coexist of ZB and WZ, WZ ZnSe nanostructure.
We use Raman spectroscopy to identify crystal structure of ZnSe one‐dimensional material (Figure 6). In sample S3, the Raman peaks at 204 and 251 cm-1 are attributed to the scatterings of the transverse optic (TO) and longitudinal optic (LO) phonon modes of ZnSe, respectively. A strong peak at 232 cm-1, between the TO and LO phonons, is thought to be surface mode. The Raman peak at ∼176 cm-1 is attributed to the hexagonal phase E1(TO) mode of ZnSe, which is inhibited in Raman spectrum (RS) of ZB ZnSe. Compared with S3, Raman peaks at 205.6 (TO mode) and 252 cm-1 (LO mode) of S1 show tiny blue‐shift. However, in S1, there is no Raman peak corresponding to the surface mode, as well as El (TO) mode, which is suppressed in the ZB phase. This indicates the existence of ZB phase in S1. Thus, structure of the sample can be shown through RS, and we got S1‐ZB phase, S3‐WZ, S2 the coexist of ZB and WZ [7] (cm-1).
\n\nFigure 7 shows the room temperature RS of CdSe/Ge‐based nanowires. The LO mode of Ge in CdSe‐Ge (or CdSe‐Ge‐CdSe), ‐CdSe‐Ge core/polycrystalline Ge sheath, and ‐Ge‐GeSe heterostructural nanowires has a downshift by 8, 5, and 2 cm-1 in comparison with that of the bulk counterpart Ge (299 cm-1), respectively. With regard to the microstructure of heterostructural nanowires, the downshift of the LO mode may be caused by tensile stress, which affects the Raman line by a downshift. And the different shift scales are attracted by the different sizes of the Ge subnanowires and Ge nanocrystalline [8].
Raman spectrum of (a) CdSe‐Ge biaxial nanowires and CdSe‐Ge‐CdSe triaxial nanowires. (b) CdSe‐Ge biaxial nanowire core/polycrystalline Ge sheath heterostructures. (c) Ge‐GeSe biaxial heterostructure nanowires.
The individual layer in SnS2 is known as an S‐Sn‐S sandwich bonded unit. Each Sn atom is octahedrally coordinated with six nearest neighbor sulfur atoms, while each S atom is nested at the top of a triangle of Sn atoms. The sandwich layers in the elementary cell occur along the c axis and bonded together by Vander Waals forces. The normal modes of vibration in SnS2 are given by the irreducible representations of the D3d point group at the center of the Brillouin zone: Γ = Alg + Eg + 2A2u + 2E2u. Two Raman‐active modes (A1g and Eg) and two IR‐active modes (A2u and Eu) are found. In view of the existence of an inversion center, the IR‐ and Raman‐active modes are mutually exclusive. On the other hand, six atoms in the unit cell of SnS2 extend over two sandwich layers. Eighteen normal vibration modes can be represented by the following irreducible form: Γ = 3A1 + 3B1 + 3E1 + 3E2. Based on the analysis above, there are six modes, which are both IR‐ and Raman‐active, belonging to A1 and El, and three Raman‐active modes belonging to E2. The B1 modes are silent, while the three acoustic modes belong to A1 and E1 [9].
\nThe RS of β‐SnS2 nanocrystal is illustrated in our former work [10]. The spectra show one first‐order peak at 312 cm-1 that corresponding to A1g mode. The RS of as‐prepared SnS2 shows a slight redshift in comparison with that of bulk materials (peak at 317 cm-1). The redshift of phonon peaks is due to spatial confinement of phonon modes. The first‐order Eg mode (peak at 208 cm-1) cannot be observed, which likely results from a nanosize effect. A wide peak between 450 and 750 cm-1, which only observed in the bulk materials at lower temperature, may be attributed to second‐order effects.
\nThe phonon dispersion of single‐layer MoS2 has three acoustic and six optical branches derivatized from the nine vibrational modes at the Γ point. The three acoustic branches are the in‐plane longitudinal acoustic (LA), the transverse acoustic (TA), and the out‐of‐plane acoustic (ZA) modes. The six optical branches are two in‐plane longitudinal optical (LO1 and LO2), two in‐plane transverse optical (TO1 and TO2), and two out‐of‐plane optical (ZO1 and ZO2) branches.
\nFor 2L and bulk MoS2, there are 18 phonon branches, which are split from nine phonon branches in 1LMoS2. The phonon dispersions of 1L and bulk MoS2 are very similar, except for the three new branches below 100 cm-1 in bulk because of interlayer vibrations. There are similar optical phonon dispersion curves for 1L, 2L, and bulk MoS2 because of the weak Vander Waals interlayer interactions in 2L and bulk MoS2 [11].
\nRaman spectroscopy is also used to accurately identify the layer number of MoS2. The frequency difference between out‐of‐plane A1g and in‐plane E2g1 mode of MoS2 is denoted as .
The phonon dispersion and density‐of‐states curves along the principal symmetry directions of kesterite CZTS were calculated using a density functional theory by Khare et al. [13]. The phonon states around 50–160 cm-1 are mainly composed of vibrations of the three metal cations with some contribution from the sulfur anions. The phonon states around 250–300 cm-1 are mainly composed of vibrations of the Zn cations and S anions with some contribution from the Cu cations. The phonon states from 310 to 340 cm-1 are mainly a result of vibrations of S anions, whereas those from 340 to 370 cm-1 are composed of the vibrations of Sn cations and S anions.
\nTo more exactly confirm secondary phases in Cu2‐II‐IV‐VI4 semiconductors, Raman scattering studies have been extensively performed. From the vibrational point of view, the zone‐center phonon representation of the kesterite structure space group I
In our work of fabrication of Cu2ZnSnSxSe4-x solid solution nanocrystallines [15], RS revealed that vibrating modes were modulated by x‐values. The peak position of 170, 189, and 229 cm-1 shifted to higher frequency with increasing x‐value in CZTSSe, respectively. Those peaks completely disappeared when x = 4. Moreover, a wide peak located at about 330 cm-1 appeared when x > 0 and the relative intensity increased with increasing x‐value. Such results indicate that Se elements were gradually replaced by S elements in CZTSSe solid solution system.
\nThis work was supported by the National Natural Science Foundation of China under Grant Nos. 11174049 and 61376017.
\nIn a never-ending pursuit to understand individual criminality and how various social factors encourage or inhibit criminal activity, criminologists developed the concept of criminal careers [1, 2]. This concept emerged from the work of Alfred Blumstein [3], who aimed to quantify offending and improve the way criminology and other behavioural and social sciences make prediction and test empirical data. Using data from previous research, Blumstein et al. developed a concept of “criminal career” in order to develop a framework through which effective crime control policies could be developed [4]. Their understanding of the concept developed from indicating individual offending frequency (λ) calculated by determining the average number of crimes committed per year by active offenders (true frequency) measuring the individual arrest frequency (the average number of arrests per year of active offenders; measured frequency – the μ). They determined that λ and μ were linked by q, a probability of arrest following a crime (μ = λ ∗q) (μ = λ ∗q) [4].
\nAt the same time, in the 1980s, the US showed an intense social and political focus on high crime rates and crime control. Due to the rise in violent crime, the US Government started a task force on violent crime which proposed increasing the federal role in the prosecution of violent crime, and other far-reaching changes in federal law including abolishing parole, expanding prisons, and restrictions on sentencing discretion [5]. To oppose these retributive measures, the National Research Council of the National Academy of Sciences organised a Panel in 1986, chaired by Alfred Blumstein, that focused on sharing knowledge and finding alternatives to this “tough on crime” policy [6].
\nThe main focus of the Panel was to develop research on criminal careers, defined as “longitudinal sequence of offences committed by an individual” [3] and to distinguish “criminal careers” from a ‘career criminal’, i.e. “an extreme group of offenders who commit serious crimes at high rates over an extended period”. A criminal career is often considered a total number of crimes with regard to the duration of offending while career criminals term refers to persistent offenders. In other words, anyone can have a criminal career while only those with the highest frequency of offending can be described as career criminals [7]. The Panel was particularly interested in whether information about an individual’s criminal career (e.g. instant offence type, a record of prior offences, including any juvenile record, drug use) could help in determining criminal sanctions. Researchers on the Panel discussed the methodological, operational, and ethical challenges involved in using predictions about criminal careers in criminal justice decision making [5].
\nCentral to the criminal career paradigm is that it recognises that individuals begin their criminal activity at some age, constitute a number of criminal offences, commit different types of criminal offences, and then desist or terminate offending. As a result, the approach to studying criminality through the concept of criminal careers emphasises the need to obtain data on why and when perpetrators start committing crimes, why they continue to offend, what is their frequency of offending, do they escalate and specialise in offending, and why and when they cease to offend [7].
\nCriminal career research has a somewhat complex organisation. It can be presented in several organising concepts that could be compared to a puzzle or branches on a tree [8]. At the beginning of the criminal career research, most researchers agreed that every criminal career has a beginning (“onset” or “initiation”), duration and end (“dropout”, “desistance” or “termination”) [9]. Additionally, criminal career concept is researched through four key dimensions - participation in offending, the individual offending frequency, the seriousness of the offences, and career length. These dimensions let to a set of related constructs and questions for researchers to explore [10]. The division into these features helps to understand, describe, and contextualise the offender’s criminal activity at a certain point in time [2].
\nDespite limitations and challenges, criminal career research shifted the focus from general to selective incapacitation strategies, trying to achieve the maximum possible crime reduction for the lowest possible cost [6]. Since its introduction to the criminological theoretical world, a significant amount of empirical, theoretical and policy-oriented research has been published [6] introducing new ways of looking at the crime phenomena such as age-crime curves [8], offending patterns, researching within-individual differences and differences between individuals [2, 6, 8]. Most importantly, investment in longitudinal research since the 1980s has contributed to creation of Developmental and Life-Course Criminology (DLC) in the 1990s [4]. Essentially, DLC is concerned with the development of offending, risk and protective factors and the effects of life events on the development of an individual by documenting and explaining within individual changes in offending throughout life [4, 8]. Although DLC theories resulted from research on criminal careers, criminal career was never established as a theory, rather as one of the paradigms of DLC.
\nMost of the criminal career research is focused on in-depth research of the criminological problems closely connected to onset, duration, and desistance from offending. In other words, criminal career research gravitated towards answering some important questions about general offending. However, little scholarly attention was given to sexual offences. Therefore, the field of sexual violence represent an important gateway to new insights and has much to offer to area of criminal career and life-course perspective.
\nIn the past, sex offender literature has largely focused on biological and psychological roots of offending making individual pathologies and early trauma the most common explanations for sexual offending. Traditional theoretical views on sexual offending describe sexual offending through trait-like features such as cognitive distortions, low victim empathy, deviant sexual preferences, poor attachment style, sexual regulation. We will here briefly present some of the most used theoretical explanations regarding sex offending.
\nOne of the major concept used in explanations of sexual offending is paraphilias who are defined as sexual disorders characterised by intense, sexually arousing fantasies involving either nonhuman objects, suffering or humiliation of oneself or one’s partner, children or other nonconsenting persons [11]. Most common paraphilias are paedophilia, voyeurism, transvestic disorder and exhibitionism [12]. However, it was found that unlike problems such as depression or anxiety, most cases of sexual offending (rape, child molestation, etc.) are not associated with any particular cluster of covarying signs and symptoms [13]. Moreover, even though some individuals who commit sexual offences against children are diagnosed with paedophilia, a mental disorder characterised by deviant sexual interests in children and some may have a paraphilia of some type, typically, this is not the case for all child sex offenders. [13]. Attachment theory, however, points out that sexual deviance is a consequence of the loss or emotional distress and intimacy deficits [14].
\nThe psychodynamic theory explains sexual deviance as an expression of the unresolved problems experienced during the stages of development, and sexual deviancy occurs when the id is overactive [14]. The function of id is to operate unconsciously and to impel the organism to engage with need satisfying activities which are experienced as pleasure. However, this explanation fails to address the cultural context of human development [15]. Similarly, biological theories focus on abnormalities in the structure of the brain, level of hormones, genetics, and deficits in the intellectual functioning of sex offenders. Many studies have shown abnormalities in the brain of some perpetrators, but there is insufficient evidence to support more generalisation of the results [16].
\nSex offending can also be studied through feminist theories focusing on the structure of the relationship between the sexes and the disparity of power between a man and a woman [16]. In general, feminist theories on child sexual abuse are divided into radical feminist perspective and post-modern perspective. Radical perspective centres on the patriarchal nature of (Western) society. Patriarchy has been defined by radical feminists as the world view that seeks to create and maintain male control over females. This perspective emphasises that sexual abuse is a representation of the patriarchy and the power that men have over women and that all men are socialised to hold attitude and exhibit behaviours that are associated with sexual offending. However, this perspective was criticised because of the lack of empirical scope [17]. The post-modern perspective rejected the radical perspective and established that men who sexually abuse are neither outside the society nor reducible to it and that they may know exactly what they are doing, but some offenders may not. This perspective was as well criticised because it is vague on what their theoretical position on sexual violence is [17].
\nEvolutionary theories, however, explain the diversity of human behaviours, including the aggression of sexual offenders as a way of adapting to changes in the environment. The evolutionary settings explain sexual aggression on sexual selection and reproductive strategies, whereby as one of the sexual strategies they cite the compulsion of sexual coercive is also present in the animal world as one of the reproductive strategies. The criminal offence of rape within these theories is a result of the inability of men to win a partner by more appropriate methods [16].
\nMore influential theories in social sciences described sexual offending through cognition and behaviour. Behavioural theories suggest that deviant sexual behaviour is the result of learned behaviour. They assume that sexual excitement plays a crucial role in sexual offences. Sexual satisfaction and lack of negative consequences of sexually deviant behaviour increase the likelihood that such behaviour will continue. If the negative effects are strong enough, the behaviour will decrease [16]. However, many male sex offenders lack deviant sexual arousal patterns [18] and other traits such as the lack of empathy for the victim or remorse which in some individuals may also play a role in the development of deviant sexual behaviour patterns [16].
\nCognitive theories suggest that cognitive distortions are the main cause of deviant sexual behaviour and that “concealed” opinion leads to “distorted” behaviour [16]. Cognitive distortions are often referred to as offence-supportive attitudes, or cognitive processing during an offence sequence, as well as post-hoc neutralisations or excuses for offending [19]. The cognitive-behavioural theory addresses how offenders’ thoughts affect their behaviour: focus on how sexual offenders diminish their feelings of guilt and shame by rationalising them through excuses and justification [14]. Although many offender rehabilitation programmes focus on eliminating cognitive distortions, the relationship between cognitive distortions and future crime is not clear and it seems cognitive distortions may not be what causes fallacious thinking at all because, outside the criminal context, “making excuses” for one’s behaviour is widely viewed as a normal thing [19].
\nSocial learning theories explain how children who are victims of sexual abuse become perpetrators of sexual offences as adults. Also, this theory states that sexually explicit materials can contribute to committing sexual offences. Furthermore, victim’s age at the beginning of abuse, the relationship between the perpetrator and the victim, the type of sexual act, the amount of coercing used, and the duration and number of victimising events all have a crucial role in the connection of acts of sexual offences and subsequent acts of sexual delinquents [16]. This theory is most often criticised because there is little evidence to suggest that children who are victimised will become abusers themselves. [20]. Furthermore, direct link between the use of pornography and sexual violence was never confirmed; however, some studies suggest there might be some connection between pornography and attitudes that support sexual aggression [16].
\nOne of the limitations of these trait-like approaches is that it comes at a cost of a broader view of sexual offending. Moreover, individual pathologies-based explanations are not well suited for a developmental and longitudinal perspective of causes for this kind of behaviour. They have also contributed to sex offender researchers emphasising the differences, rather than searching for the similarities between sexual and nonsexual offending [6]. Criminal career approach provides a more developmental point of view explaining how sexual offending starts, develops, and stops as well as whether such distinctions are theoretically, clinically, and/or policy relevant [2]. In other words, maturation and dynamic theories assume that the same mechanisms underlie the behaviour of all offenders while life-course criminology emphasises the need to use a more broader view on the causes of sex offending as well as to find similarities between the perpetrators of these crimes rather than differences.
\nThe most important theoretical question that needs to be answered when studying sex offenders through criminal careers is whether sex offenders should be regarded as similar or different from non-sexual offenders in terms of the aetiology of their offending behaviour. Consequently, there are two possible ways to consider sexual offending- that it is different from non-sexual offending and that it is an integral part of the general offending repertoire.
\nIf studied separately, one possibility is to distinguish adolescence-limited from persistent sex offenders. This way of studying offenders gained its popularity in the 1990s with Moffit’s Dual Taxonomy theory [7]. This theory states that adolescence-limited antisocial behaviour individuals have brief criminal careers, lack consistency in their antisocial behaviour across situations and may also have irregular, crime-free periods. Adolescence-limited delinquents are likely to engage in antisocial behaviour in situations where they estimate they could gain profit, but they also abandon antisocial behaviour when prosocial behaviour is more rewarding.
\nAdolescence-limited offenders usually start offending by the ways of three distinctive conditions: motivation, social mimicry and reinforcement. Social mimicry is a term taken from the ethology and is loosely connected to the social mirroring theory. Adolescents often mimic the behaviour of their life-course-persistent peers in order to gain the same benefits (i.e., status in the peer groups; friends, etc.). In other words, adolescence-limited offenders commit criminal offences if they can gain from them, and if such behaviour is reinforced by their peers. With a change in their circumstances, for example, starting college or starting a job, they will usually stop offending [7].
\nIndividuals that fall under the category of life-course-persistent antisocial behaviour exhibit antisocial behaviour at an early age. For example, biting and hitting at age 4, shoplifting and truancy at age 10, selling drugs and stealing cars at age 16, robbery and rape at age 22, and fraud and child abuse at age 30; the underlying disposition remains the same, but its expression changes form as new social opportunities arise at different points in development. The Dual taxonomy theory, however, does not suggest that all specific behaviours in childhood will be predictive of criminal behaviour in adulthood, but that it might be associated with behaviours that are conceptually consistent with the earlier behaviour [7].
\nBeyond young adulthood, the antisocial disposition of life-course-persistent may be expressed in a form that is not yet well-measured (e.g. neglect and abuse of family members). According to this theory, it is necessary to investigate the roots of antisocial behaviour in the early life of life-course-persistent offenders. Moreover, some of the causes for life-course-persistent offending are neuropsychological (disruption in the ontogenesis of the fetal brain, minor physical anomalies, maternal drug abuse, poor prenatal nutrition, exposure to toxic agents, brain injury because of complication during delivery), variability in infant temperament, developmental milestones and cognitive abilities, exposure to criminogenic environment or inconsistent discipline. Thus, over the years, an antisocial personality is slowly constructed. Likewise, deficits in language and reasoning are incrementally elaborated into academic failure and insufficient job skills. Over time, all the problems accumulate, and an individual has fewer options for change. This theory of life-course-persistent antisocial behaviour emphasises the constant process of reciprocal interaction between personality traits and environmental reactions to them [7].
\nHowever, if sex offending is studied combined, the question is to what extent sexual offending (or which type of sexual offending) is characteristic of a particular overall offending trajectory. Furthermore, it might be necessary to study sexual offenders by dividing them into different offence types as they may be stemming from different causal processes and thus it would be best to consider their different developmental pathways [6].
\nCurrent research suggests that there are some significant differences between sex offenders and non-sexual offenders. For example, the prevalence of general delinquency peaks in adolescence while sex offenders have two peaks in offending, one in adolescence and on in the mid to late 30s [6, 21, 22]. Also, sex offenders show continuity in general offending and antisocial behaviour, but low continuity in sexual offending [22]. This finding resonates with the finding that delinquency is usually just a part of a larger behavioural repertoire consisting of potentially harmful behaviours such as substance misuse [21]. Similarly, non-sexual offences usually precede sexual offences and specialisation in sex offending does not increase in adulthood [6, 22]. Therefore, criminal career offers an interesting way of studying offending patterns by looking into the four key dimensions (participation, frequency, seriousness, and length [3, 4, 9, 10, 23] and related constructs such as escalation, specialisation, co-offending, intermittency, and others [2, 9, 24, 25].
\nThe dimension of participation refers to the proportion of a population who are active offenders at any given time, while frequency refers to the average annual rate at which this subgroup of active offenders commits crimes. In other words, participation refers to the prevalence of offending, while frequency refers to the incidence of crime [26]. Both dimensions are particularly difficult to research and estimate because of the underreporting of sexual offences and the so called “dark figures” of crime. Nevertheless, frequency has been of particular interest to the policymakers as it implicated that it is possible to identify high-frequency offenders and incapacitate them to maximise the incapacitation effect. However, it appears that the frequency of offending is very complex and that its value might fluctuate throughout a criminal career [27]. Another difficulty with the dimension of frequency is that it is challenging to estimate. For instance, one sex offender can offend against one victim over a, for example, 5-year period, multiple times, but official reports will note his offences as one offence.
\nThe Cambridge study [28] found that the prevalence and frequency of sex offending in community samples is low and that that there is little evidence of recidivism or continuity. With respect to the prevalence and frequency of sex offending, conviction data indicated that whereas 41% of the males in the sample had been convicted by age 50, only 2.5% of the males had a conviction for a sex offence.
\nHowever, self-report and victimisation studies show a much higher number of individuals participating in sexual offending. For instance, The Bureau of Justice Statistics’ (BJS) in the US conducts a National Crime Victimisation Survey (NCVS) [29] every year using a nationally representative sample of 240,000 interviews on criminal victimisation. Results for 2018 showed that the rate of rape or sexual assault victimisation increased 1.6 to 2.7 victimizations per 1000 individuals aged 12 or older in comparison to previous years. Even more concerning data emerged from two meta-analyses [30, 31] of 282 studies around the world on child sexual abuse. The analyses used self-report data and found that the prevalence of child sexual abuse ranges from 12.7–19.7% for girls and 7.6–7.9% for boys. Both analyses showed that the highest prevalence of sexual abuse of children is in Africa and the lowest prevalence rate in Europe.
\nIt is important to point out that sexual offences are often generalised as heterosexual offence [32] and therefore, there is very little known about male victims [33]. Recent figures indicate that around 12,000 males are victims of sexual assault or rape in the UK every year [34] and that nearly 1 in 4 men in the U.S. experienced some form of contact sexual violence in their lifetime. Among male victims of complete or attempted rape, about 71% experienced such victimisation before the age of 25 [35].
\nThe frequency of offending varies significantly depending on the used method and between types of sex offenders. Sex offenders against women have, on average, 1.8 victims, whereas extra-familial child abusers have 3.4 victims on average [36]. Another study [37] suggests that sexual offenders with adult women victims had, on average, 2 official victims, but self-reported close to 12 victims. Similarly, sex offenders who offended against children had, on average, officially offended against 2 victims, but self-reported 7 victims.
\nFinally, investigations into the frequency of prolific, persistent sex offenders using several sources of information (i.e., self-reports, police investigations, victim statements) came up with three key conclusions on sex offending [38]. Firstly, about 11% of the sample committed over 300 sex crime events as opposed to about 40% who committed only one sex crime event. Secondly, some offenders take advantage of low-risk short-term opportunities with different victims, while others exploit a single offending opportunity by repeatedly offending against the same victim over a certain period of time. Thirdly, the findings revealed that the most prolific sex offenders were older, had a more conventional background characterised by a stable relationship with an adult partner, a job at the time of the offence (s), no drug issues, and no prior record for a sex crime.
\nThe third dimension of the criminal career, seriousness, is in some ways, fundamental for criminal career research. Seriousness refers to the level of seriousness of the offences being committed by a given individual [3] and takes the modern approach to crime by focusing on determining a level of risk. Risk relates to the probability of criminal behaviour and is usually measured as low, moderate, or high [39, 40]. Offender risk is usually determined based on the possibility of reoffending or recidivism. It is important to define two categories here: chronic and recidivists [41]. The chronic type offenders are more at risk of persistent life-span criminal careers, which are costlier to society; over time they may have more victims (and financial loss for the victims) in addition to the costs associated with their arrest and incarceration. Recidivists are less persistent, as they have a lower incidence of reoffending. However, the categories do not differentiate on the severity of offences, only on offending timespan.
\nOffenders that maintain lengthier periods of offending tend to be generalists in their criminal behaviour [42, 43], their offences may be less severe than those that commit more severe types such as rape, sexual homicide, or child abuse. While there may be differences between types of reoffences (i.e. fraud and sex offences), society is risk-averse to more salient offences such as rape and child molestation [44, 45]. However, meta-analyses reports show that public fear of sexual offenders is often misplaced, and that offender’s recidivism rates for sexual offences vary between 11,5% and 13,7% while general recidivism rate varies between 33,2% and 36,2% [46, 47].
\nSome authors argue that these four key dimensions of criminal career, and especially seriousness, made it possible for a variety of important theoretical opportunities to emerge along with research on criminal careers [48]. This segment of criminal careers has several parameters that are observed through the dimension of seriousness: the severity of the criminal offence, escalation, specialisation, and crime-type switching [49].
\nThe severity of the offence refers to the tendency towards committing severe criminal offences during a criminal career while escalation refers to the tendency towards making initial minor offences towards the increasingly more severe offences [27]. Escalation reflects the concern that as the career develops, the offender engages in more serious offences. There are different causes for escalation, for example, experience, increasing boldness or a stressful experience [6, 27].
\nEscalation research emerged interesting findings such as that most sex offenders who perform masturbation in front of their victim do not switch to a different sexual act (for example intercourse) when they abuse their second victim [50]. This finding points out that sex offenders tend to specialise in a particular sexual act and that they are not likely to escalate their sexual offending from non-contact to contact offending, for instance.
\nAnother interesting finding [51] suggested that victim resistance plays a significant role in whether or not offenders will de-escalate in the amount of physical force used between victims. If the first victim resisted the offender, he was more likely to de-escalate in the level of physical force used. However, if the second victim resisted, the offender was less likely to de-escalate, indicating that he is adopting more force to secure subsequent victims if there is resistance. Furthermore, sex offenders who consume drugs in the hours before the first crime are more likely to de-escalate in the level of physical force used than be stable.
\nCrucial to determining behaviour consistency is the way an offender sources his victims. The “hunting” process is an essential stage of the sexual assault and offenders who find their victims through their relationships, or their occupation will often repeat their behaviour in their future crime. In contrast, offenders who find their victims more spontaneously are less likely to repeat this “hunting” method [52].
\nSpecialisation is an aspect of criminal careers and is defined as likely repetitions of the same type of criminal offence [23] while versatility reflects a tendency to commit a broad array of offences without concentrating on a specific behaviour. Researchers use a “crime-switch” matrix, a matrix of crime types reflecting the probability that an offender who has previously committed one crime type will next commit a different type [27]. Research showed that there is a relationship between higher frequency of offending and versatility, but also that offenders who start offending at an early age tend to be involved in a diverse array of offences [6]. Most criminal careers are diverse, but there is some evidence of specialisation [21].
\nSex offenders in specific show little empirical evidence of specialisation, but they are characterised by persistent criminal activity and tend to show criminal diversity in non-sexual crime types [53]. It was also found [54, 55, 56] that there are substantial differences between sex offenders regarding victim type. Sexual offenders against adults have more versatile criminal records [54, 55, 56], are more violent and have a higher frequency in offending [56] than abusers of children. The other group tends to be more specialised, have a higher frequency of sexual crimes, but also tend to be criminally versatile [45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56]. Extrafamilial child molesters are consistently found to specialise more in sexual offences [54, 55]. Overall, neither child abusers nor sex offenders against adult women have a specific type of victim and that the majority of both types typically commit more non-sexual offences than sexual [56].
\nThe last dimension of criminal career research is the length; that is the time that an individual is actively offending. Research on the dimension of length attracted the attention of the scholarly community from the very beginning of criminal career research. It incorporates three head characteristics of criminal careers: beginning (“onset” or “initiation”), duration and end (“desistance” or “termination”) [2, 10].
\nThe relationship between age and crime is of an asymmetrical bell shape (most commonly known as the “age-crime curve”), showing that the prevalence of offending tends to increase from late childhood, peaks in the teenage years (around ages 15–19), and then declines from the early 20s, often with a long tail [22]. Most offenders desist during late adolescence and early adulthood, irrespective of the age of onset [22], but an early age of onset appears to be connected to a relatively long criminal career [6, 50]. Research on recidivism shows that sexual offending decreases with age, as well as general offending, and the recidivism of sexual offenders that offend against adult decreases from early adulthood [57, 58]. However, unlike the general offender, sexual offenders usually start committing offences either in adolescence or in mid to late 30 [2, 59].
\nSome of the possible explanations of why sex offenders appear to be older when they start offending include that there is a high rate of unreported sex offences because the victims are less likely to report sexual offences than non-sexual offences and because there is a disbalance between official statistics and self-report. A gap between the age of onset in the official statistics and self-report is seven years [2]. Moreover, nearly 20% of sexual offenders are at the end of their criminal career, or their career has already desisted when they are convicted of their first sexual offence [2].
\nAlternatively, some authors [60] suggest that the discrepancy that goes against the logic of the life-course explanation of desistance could be explained by increased average ages of marriage and parenthood. In specific, the peak in sexual offending seems to occur at a time when adolescents already transitioned into adulthood which could mean that sex offenders do not transition into adulthood at the same pace as non-sexual offenders, or that these transitions do not affect recidivism in the same way as they do non-sexual offenders. Besides the transition into adulthood, several other reasons could influence individuals to start with sexual offending. For example, loneliness is commonly reported among sex offenders, that the transitions that influence common crime do not affect sexual offending (or affect it to a lesser extent), a cost-benefit analysis that makes sex offenders less likely to accept the cost of being labelled as a sex offender, conflicting interpersonal relationships, and maturation factors [60].
\nThe above-described factors could affect the length of a criminal career, but the most significant variable affecting the length of a criminal career is the age of the first conviction. The likelihood of termination of offending is noticeably different as the age of the first conviction rises, and more severe offenders cease to offend after the first conviction only in fewer cases [61].
\nThe dynamic concept of criminal careers empowered researchers to develop a whole new way of looking at crime. Traditional criminological theories offered a rather static explanation of one’s criminal conduct, while criminal career concept offered a view on criminal conduct that can be used to explain crime on an individual and group level. Furthermore, based on that, a new set of criminological theories emerged based on that concept, a Developmental and Life-Course Criminology, which emphasise a more dynamic approach to the aetiology and phenomenology of criminal conduct.
\nThe main advantage of the criminal career concept regarding criminal conduct is that it offers a different perspective on criminality which can be used as a “bridge” between theoretical criminology and policy-relevant research. As we have shown on the example of perpetrators of sexual offences, there are differences in the development and peculiarities of the criminal career of these perpetrators. What the theories based on the concept of criminal career can offer are different explanations of the aetiology and phenomenology of these perpetrators about the particularities of their individual criminal careers. In this way, perpetrators can be viewed in terms of similarities and differences in the dimensions of a criminal career which can have multiple benefits. Specifically, although it is the same group of criminal offences, it is possible to have different theoretical explanations for the emergence and development of particular subgroups of perpetrators of certain criminal offences. In this way, specific prevention policies can be created that can be more effective because they identify not only the factors that influence the occurrence and development of certain types of crimes, but also the dynamics of the relationship between risk and protective factors that contribute to it. In this way, interventions at any level in terms of prevention and rehabilitation of offenders can be more successful.
\nAnother great advantage of the concept of criminal career is that it allows the creation of new explanations of the origin and development of certain crimes, which contributes to the development and emergence of new criminological theories and concepts that, taking into account traditional explanations of crime and achievements of criminological research, could contribute to a new theory by erasing the understanding of committing crimes within the concepts of “traditional” and “newer” theories, but finding new ones that can merge all previous concepts into one that best suits the specifics of a particular crime or perpetrator.
\nIt appears that only fractions of the concept and DLC theories are seldomly studied, causing the lack of comprehensive theory and resulting in some aspects of criminal careers not being researched enough while other areas are receiving more focus. This is true if we look at the types of crimes that are the focus of research under the concept of criminal career. The commission of sexual offences is now relatively unexplored and research to date has covered a small number of countries, mostly in the developed countries of the west. Therefore, the findings mentioned in the chapter need to be considered from the context of these countries. We hope that there is going to be more international collaboration and more scholarly focus on this topic in the years to come.
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