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Data collection and monitoring: Summarising the challenges

The challenges in collating data on human trafficking and slavery in a form that does more than ‘stat(e) that trafficking is a problem’ (Lazcko 2005: 14) are well recognised (see, for example, Ali 2010; Aronowitz 2009; GAO 2006; Goodey 2008; Lazcko 2007, 2005; Lazcko & Gramegna 2003; Tyldum 2008; Tyldum & Brunovskis 2005; UN.GIFT 2008). As noted earlier, these challenges largely relate to the collection of reliable and complete data that can adequately address the complexities of these crimes and hence provide a fuller understanding of how it manifests and the appropriateness and adequacy of responses. Of equal importance is the means to consolidate this data to allow for the examination of patterns and trends, to promote ease of interpretation and to improve the dissemination of findings. As a prelude to describing the factors for consideration if a monitoring program on human trafficking and slavery was to be established, key themes that have emerged from developmental work undertaken elsewhere to improve data collection and monitoring of human trafficking and slavery are presented here.

Challenges

Regardless of content or use, data on human trafficking and slavery must be relevant, regular, reliable, protected and turned into meaningful information (David 2007). The two main challenges to reliable and accurate collection of data on human trafficking and slavery involve the nature of the crime itself and the nature of available data. The two are intrinsically linked, in that the nature of the crime can have a direct influence on the type and completeness of data available.

Nature of the crime

Various elements of human trafficking, slavery and slavery-like practices hinder the collation of data that captures the scope of these crimes. These crimes are underreported, under-detected and under-prosecuted, with the majority of human trafficking and slavery victims and offenders largely hidden (Laczko 2005; Tyldum & Brunovskis 2005). Low levels of reporting can be attributed to:

  • the reluctance of victims to report their exploitation due to fearfulness of reprisals against themselves or their families;
  • a lack of awareness of how or where to report the abuse;
  • distrust of law enforcement and criminal justice authorities; and/or
  • uncertainty as to whether a response will ensue and if that response will be favourable to them (eg the risk of deportation has been identified as a key reason for victims failing to report; Goodey 2008).

People may also be reluctant to identify as victims of human trafficking, slavery or slavery-like practices. This could be related to the stigma associated with being a victim of these crimes, or a lack of understanding about which practices amount to exploitation.

Low detection rates are also related to difficulties, particularly experienced by some of those who come into contact with victims, of understanding or interpreting the circumstances being presented to them as constituting human trafficking or slavery-like practices (see, for example, David 2010; Joudo Larsen et al. 2012; Richards & Lyneham 2014). Education and awareness training among frontline personnel, service providers and the broader community have likely improved identification but will continue to affect what is officially reported and recorded.

The covert nature of human trafficking and slavery also produces information that is subject to ‘institutional bias’ in that the information available is largely based on what is able to be derived from a mix of court transcripts, investigative material, countertrafficking agencies or relevant non-government organisations (Andrees & van der Linden 2005). While these data are often the only material available to illustrate the nature and extent of human trafficking and slavery, it must be recognised that they may be unrepresentative or constitute a somewhat misleading representation of these crimes, both in volume and practice.

Nature of the available data

The other major challenge in monitoring human trafficking and slavery is the availability of data, and where data exists, its consistency and completeness. Other attempts to develop or enhance human trafficking and slavery monitoring programs, including the AIC’s previous monitoring reports, have described the range of obstacles commonly uncovered in developing data collection and indicator frameworks, including:

  • a lack of comparable and consistent data;
  • incomplete data;
  • an absence of ongoing or uninterrupted data collection (ie absence of time series data);
  • fragmented data collection systems;
  • a lack of common definitions within and between existing data sources;
  • inconsistent identification of victims across different data sources (eg victim services compared with law enforcement data);
  • a narrow spectrum of human trafficking and associated exploitation scenarios captured in the data;
  • double counting within and between existing data collection systems; and
  • deficiencies in information sharing.

It is important, however, to separate the challenges involved in international versus domestic data collection. Internationally, a key issue for data collections is the lack of specific human trafficking and slavery legislation in some jurisdictions (UN.GIFT 2008) and where legislation does exist, the lack of consistency in terminology used within legislation and policy (see, for example, Stefanizzi 2007 and the focus of human trafficking legislation in some countries on sexual exploitation). This can detrimentally affect the capacity for valid comparisons of official data at an international and regional level. The provision of a detailed definition of human trafficking within the UN Trafficking Protocol has been an important step in addressing this inconsistency (Kangaspunta 2007), with Member States obliged to introduce legal definitions consistent with the Protocol definition. However, the UN Protocol’s definition of trafficking has its limitations. It identifies human trafficking as a process that involves three stages (action, means and purpose), introducing a wide range of situations that may not always be picked up (Laczko & Gramegna 2003). In addition, the Protocol does not provide a definition of ‘exploitation’ per se but instead outlines the minimum conditions that constitute exploitation. Some of these conditions however, such as the ‘exploitation of the prostitution of others’, are open to interpretation by ratifying States.This is less the case for the definition of slavery, with a definitive delineation of slavery outlined in the Slavery Convention.

Domestically, data collection on human trafficking is often fragmentary in content and purpose, and in Australia this is no exception (Joudo Larsen et al. 2012; Joudo Larsen, Lindley & Putt 2009). Data collection generally occurs at points of contact with immigration, law enforcement, victim or migrant services. These data are collected with different objectives and variable processes in collating and recording information has resulted in a lack of standardised and systematic compilation of data across collection points. This potentially affects the validity and comparability of both time series data and data sourced from different collections. Not only does the fragmentary nature of the available data create difficulties in constructing a harmonised database, it also increases the risk of double counting incidents, victims and offenders, as well as describing characteristics on a narrowly defined population group.

The domestic definition of human trafficking has also evolved with time. In trend analysis, long-term data collection of comparable variables and outcomes must be attained in order to create an accurate view of the dynamism of the crime, such as changes in offenders’ modus operandi, victims’ country of origin, trafficking routes and methods of entry. This provides a finite timeline in which monitoring human trafficking and slavery can begin with validity.

Addressing data challenges: Best practice principles

The challenges to reliable and accurate data collection can be dealt with on two levels. The first is to identify the data items collected by different sources, determine which items are best suited to the purpose of monitoring and to foster the dissemination of existing data by implementing new or reviving lapsed data sharing arrangements as a first step to collation. The second is to improve future methods of collection by identifying where information gaps exist, standardise definitions for data items and develop data provider and custodian protocols to streamline collection practices and purposes. Before these steps can be taken, however, there needs to be an assessment of what constitutes good human trafficking and slavery data, rather than merely assembling whatever is available. David (2007) identified four ‘best practice’ principles to guide the improvement of data on human trafficking. These principles stipulate that data be relevant, regular and reliable, protected and turned into information and knowledge. While these principles were developed largely to inform the creation and maintenance of individual, agency-specific data collections, they are equally pertinent to the establishment of a monitoring dataset. These data qualities are summarised below.

Relevant data

Data must be relevant to the purpose of collection (David 2007). The objectives of data collection and monitoring, and in due course the intended analysis and knowledge expected to be gained from that analysis, need to be clearly outlined in order to identify which data are most relevant. There is also the need to identify what data are available, the original purpose and scope of these data, and how these data might be interpreted. Finally, it is important to determine the appropriate unit of observation and the appropriate unit of analysis (ABS 2013a, 2013b; Aronowitz 2009) for any variable included in the final dataset.

Regular and reliable data

To be relevant, data should be timely. The data collected and reported must be current and therefore reflect existing situations, particularly if the purpose of collection is to inform policy and operational requirements. For this to be attained, data collection must be consistent and regular.

Any collection of data must be underpinned by precise definitions and clear collection standards that are well documented in their implementation. The best practice method for information to be turned into reliable and valid data is to construct a coding frame (ie structure of variables and subcategories) outlined in a codebook, data dictionary or similar (Ekblom 1988). A data dictionary defines collected variables, specifies response items and outlines the data input process. Additional measures that ensure the reliability of data includes systematic cross-checking of coding sequences and data frequencies to identify and address any errors made during the collection or input stage.

Protected nature of the data

The confidential nature of data, particularly victim data, is an issue relevant to any data collection on human trafficking and slavery. As noted by David (2007), inadvertent release of personal information can have consequences for the persons or agencies the information was collected from or about, as well as potentially having broader implications for anti-trafficking efforts. Issues of confidentiality and the protection of data will be addressed in a later section but preferably, collated data should be de-identified and consist only of personal information items that are genuinely essential to the monitoring effort.

Meaningful analysis and implementation of systematic collection

The identification of trends, examination of long-term comparisons and the monitoring of change in the human trafficking and slavery process, and the actors within this process, is vital for the formation of a realistic picture of these crimes and the appropriate evaluation of responses. Ideally, data from various sources needs to be collated following best practice principles (such as those outlined above) and recorded in a centralised database for this analysis to be achieved. The aim is to have an efficient and consistently updated dataset—a ‘single national data pool’ (Aronowitz 2009: 38)—from which data can be easily extracted, analysed and ‘turned into information’ (David 2007: 8). Administration of the dataset by a ‘single institution…responsible for storing, processing and analysing the collected data’ (Aronowitz 2009: 38) represents the most practical option, albeit one dependent on the practicality of sourcing and compiling data from multiple sources. Such an arrangement, where supported by an information-sharing covenant, streamlines data transmission, protects data maintenance and moderates issues with data aggregation and statistical treatment.

Current measures

Current measures to monitor human trafficking and slavery have focused on developing tools to standardise and enhance existing operational data that is collected by various international, government and non-government agencies. The European Commission, United Nations Office on Drugs and Crime (UNODC) and other international organisations such as IOM and ILO have been at the forefront of collating global and regional data on human trafficking and slavery. On a state basis, the United States, the Netherlands and Germany, among others, have also initiated actions, in different guises and for different purposes, to collect data on identified cases of human trafficking. Some examples of current or proposed data collection tools on human trafficking and slavery are shown in Table 2 and described in more detail below.

Byproducts of these measures include the construction and use of tools such as data collection guidelines and minimum datasets (see, for example, ICMPD 2010, 2009; ILO 2012). In addition, templates (as part of a suite of IT resources) have been developed for operational use among European government and non-government agencies, and organisations. These templates enable a range of agencies to input information about human trafficking incidents according to variables that reflect identified indicators of human trafficking, slavery and slavery-like practices (see Vermuelen & Paterson 2010). The development of interview procedures, for example, the screening interview form used by IOM to collectdata on trafficked victims for their Counter-Trafficking Module database (CTM), is another tool constructed specifically for the collection of data.

These procedures facilitate the consistent and regular input of data that is in accordance with standardised definitions. They also provide a mechanism to share comparable data between countries and regions, and provide a framework for organisations to understand human trafficking according to a consistent definition. Further, the use of templates aids the procedure of crosschecking and validating information by providing a comparable structure to store information (including the source of information).

Table 2 Selected data collections on human trafficking and slavery
Organisation/country Name of data collection/indicator set Type of collection Level of collection Status
IOM Counter Trafficking Module (CTM) Database Statistical Regional Ongoing
ICMPD Data Collection and Harmonised Information Management Systems (DCIM & DCIM-EU) Statistical Regional Trialled
ILO Operational indicators of Trafficking in Human Beings Information and statistical Global Ongoing
US Department of Justice (US DoJ) Human Trafficking Reporting System (HTRS) Statistical National Ongoing
Institute for International Research on Criminal Policy (IRCP) SIAMSECT and MONTRASEC—Human Trafficking Reporting System Statistical Regional Trialled
UNODC Global Report on Trafficking in Persons Information and Statistical Global Ongoing
National Rapporteur on Trafficking in Human Beings (the Netherlands) National Rapporteur on Trafficking in Human Beings Statistical National Ongoing
Germany Bundeskriminalamt: National Situation Reports on Trafficking in Human Beings Statistical National Ongoing
European Commission EUROSTAT Trafficking in Human Beings Statistical Regional Ongoing
UNODC Case Law Database Information and statistical Global Ongoing

The following briefly describes select international examples of data collections maintained or proposed to collect information on human trafficking and slavery. A comparison of indicator selection across these data collections is shown in Appendix A.

IOM Counter Trafficking Module database

The IOM CTM database registers information gathered from the organisation’s interactions with human trafficking victims via their regional direct assistance, voluntary return and reintegration programs. The data are obtained from standard interview forms used in the Screening and Assistance questionnaire to populate a core set of 18 indicators that represent the ‘…very minimum base to assist in the screening process that determines whether a person has been trafficked’ (Aronowitz 2009: 45). These indicators are used to describe victim and offender profiles (see Table 3), pathways and movement, means of coercion, control and exploitation, and responses from the criminal justice system and support services.

Table 3 IOM CTM database indicators
Theme Indicator
Victim of trafficking profile Gender
Age
Citizenship
Ethnicity
Marital status
Children
Education
Socioeconomic status
Trafficking process Entry into migration/trafficking process
How individual entered the process
Recruitment status
Method of contact initiated between victim and recruiter
Profile and functions of traffickers
Means of control
Movement process
Exploitation Type of exploitation
Length of exploitation
Means of control
Response to the victim Referral mechanism
Types of assistance to victim and family
Law enforcement action

Source: Aronowitz 2009

In partnership with the Federal Ministry of the Interior of Austria, IOM developed guidelines for the collection of data on victims of human trafficking, which proposed the use of the core indicator set to promote comparability and established data requirements to populate these indicators (Aronowitz 2009). Those data recommended for inclusion in a minimum dataset are listed in Table 4. The guidelines also describe additional variables to be included in a more comprehensive data collection.

Table 4 IOM recommendations for a minimum dataset cont.
Theme Data items
Victims Individual victims
Gender
Age at time when exploitation began
Nationality
Country of birth
Country of origin
Country of recruitment
(Legal) status in country of exploitation
Type of exploitation
Retrafficked victim
Annual total number
Number of victims identified
Number of victims refused assistance
Number of victims declining assistance
Number of victims accepting assistance
Number of victims receiving temporary or permanent residence permits
Number of victims repatriated (from-to and to-from)
Traffickers Individual traffickers
Gender
Nationality
Country of birth
Age at time of committing crime
Prior status as a victim
Legal status in country at time of committing crime
Member of network or organised crime group
Annual total number
Trafficking process Type of recruitment
National borders crossed (travel routes)
Forms of border crossing
Use of fraudulent documents
Type of exploitation
Means of control over victim
Countr(ies) of exploitation
Criminal justice responses Number of persons arrested
Number of persons charged/charges
Number of persons prosecuted/charges prosecuted under
Number of persons conviction/charges convicted for
Number of persons acquitted/of which charges
Number of persons involved in claim for asset confiscation
Sentences
Number of investigations started
Number of investigations successfully completed
Number of victims cooperating with law enforcement
Number of victims testifying in court
Number of victims filing claim for compensation

Source: Aronowitz 2009

ICMPD Data Collection and Harmonised Information Management Systems (DCIM and DCIM-EU projects)

The ICMPD, associated with the European Union Data Collection and Harmonised Information Management Systems, undertook a project investigating best practice data collection, management and analysis of human trafficking data in selected European countries. The DCIM and DCIM-EU projects arose from the recognition that there were critical issues with data on victims and ‘traffickers’, and a need to achieve a higher standard of data that was available, reliable, standardised and sustainable (ICMPD 2009).

The aim of the DCIM and DCIM-EU projects was to build the competence of specified countries in the collection of victim-based and offender-based data on human trafficking, with the overall intent to support, facilitate and measure the effectiveness of government and inter-government action plans on combating human trafficking (ICMPD 2010, 2009). The resultant handbooks—one for project implementation in 10 South Eastern European countries (ICMPD 2010) and the second for the Czech Republic, Poland, Portugal and the Slovak Republic (ICMPD 2009)—provide a guide on methods of data collection, transmission, validation, protection and storage, and a recommended catalogue of data variables for inclusion in a victim-based or offender-based data collection. The handbooks were intended for use by institutions that undertook the actual collection, analysis and reporting of data on human trafficking victims and offenders, as well as institutions that may provide data for analysis as part of a larger data collection. While the context for the projects was to target government institutions, it was anticipated that the handbooks would also act as a helpful resource for other anti-trafficking actors working with data collection and management systems, from both criminal justice and victim protection, and assistance perspectives (ICMPD 2010, 2009).

Victim data should be collected on ‘identified’ victims of trafficking. Data on traffickers should focus on individuals who have a trafficking or related charge registered against them, either in the form of a complaint or an actual arrest (ICMPD 2010). A list of the suggested variables to be collected in a victim and offender-based database is shown in Tables 5 and 6 respectively. Victim variables annotated with an asterix are those recommended by the ICMPD for inclusion in a minimum data set on victims.

Table 5 Data items for inclusion in victim-based database (DCIM and DCIM-EU) cont.
Theme Data items
Case registration Registering entity*
Date when case registered
Source of information*
Victim’s background Gender*
Date of birth and/or age
Education level
Citizenship*
Country of residence
Area/region of origin
Demographic setting
Marital status when trafficked
Marital status when detected/flagged or identified
Number of children when trafficked
Contributor to household income before trafficking
Activity at recruitment*
Motivation for migrating/leaving home
Recruitment experience Age/date at recruitment
Country of recruitment
Means of recruitment/entry into trafficking*
Victim’s relationship to recruiter
Gender of recruiter
Recruiter’s citizenship
Recruiter’s country of residence
Proposed destination country at residence
Transportation and travel routes Means of transportation
Border crossings
Use of documents
Attendance of traffickers during travel/transportation
Exploitation experience Forms of trafficking/exploitation*
Forms of control when trafficked*
Date when trafficking exploitation began
Legal status (in national territory) at time identified as a victim
Date exited trafficking/exploitation
Means of exit from trafficking/exploitation
Previous experience of trafficking
Year of previous trafficking/exploitation*
Form of previous trafficking/exploitation
Country of previous trafficking/exploitation
Identification/assistance during previous trafficking
Identification, assistance and cooperation Country/district/place of residence at current country
Country/district/place of activity at current country
Location where victim was detected/identified*
Assistance received*
Date entered assistance*
Date exited assistance*
Type of assistance
Transferred to other service providers
Received services in the past*
Legal status in the national territory at the end of assistance
Statement to police
Testifying in legal proceedings against the trafficker
Protection pre, during or post trial
Victim compensation*
Return to country of origin*

Source: Adapted from ICMPD 2010

Table 6 Data items for inclusion in offender-based database (DCIM and DCIM-EU)
Theme Data items
Case registration Registration number/code
Trafficker’s name
Date when case registered
Source of information
Alleged/convicted trafficker’s background Gender
Date of birth and/or age
Citizenship
Country of residence
Area/region of origin
Role in the trafficking chain
Investigation phase Date case initiated
Location where case initiated
Initiation method
Date investigation commenced
Date investigation completed
Date of arrest
Charges at arrest
Type of trafficking exploitation
Number of victims involved
Number of victim statements
Trial phase Location of court and crime process
Date when crime process entered the trial process
Date when crime process ended in the first court
Charges at trial
Trial outcome
Type of sentence imposed at trial
Duration of sentence (at trial)
Fine imposed (at trial)
Appeal process Conviction appealed
Date appeal commenced
Date appeal concluded
Grounds for an appeal
Petitioner of appeal
Result of an appeal process
Sentence imposed (at appeal)
Duration of appeal sentence
Fine amount (at appeal)
Post-trial phase Final sentence implementation
Victim compensation orders

Source: Adapted from ICMPD 2010

Ineternational Labour Organization’s operational indicators of trafficking in human beings

One of the most well recognised indicator sets relating to human trafficking was developed by ILO, in conjunction with the European Commission, to measure the extent of trafficking of adults and children for labour and sexual exploitation (see ILO 2009). The operational indicators were developed through the application of the Delphi methodology, which sought widespread expert opinion to form consensus on indicator content and definition. A total of 67 indicators were identified, applying to the labour exploitation or sexual exploitation of adults or children. Indicators are graded according to whether they represent a strong, medium or weak indicator of deceptive recruitment, coercive recruitment, recruitment by abuse of vulnerability, exploitative conditions of work, coercion at destination and abuse of vulnerability at destination. These represent six dimensions of the human trafficking definition. For a victim to be assessed as a potential victim of trafficking, the following must be recorded:

  • two strong indicators;
  • one strong indicator and one medium or weak indicator;
  • three medium indicators; or
  • two medium and one weak indicator.

An example of these indicators is shown in Table 7, which lists indicators of trafficking of adults for labour exploitation.

Table 7 ILO indicators of trafficking of adults for labour exploitation
Dimension Indicator strength Indicator
Deceptive recruitment Strong indicator Deceived about the nature of the job, location or employer
Medium indicators Deceived about conditions of work
Deceived about content or legality of work contract
Deceived about family reunification
Deceived about housing and living conditions
Deceived about legal documentation or obtaining legal migration status
Deceived about travel and recruitment conditions
Deceived about wages/earnings
Deceived through promises of marriage or adoption
Weak indicator Deceived about access to education opportunities
Coercive recruitment Strong indicator Violence on victims
Medium indicators Abduction, forced marriage, forced adoption or selling of victim
Confiscation of documents
Debt bondage
Isolation, confinement or surveillance
Threat of denunciation to authorities
Threats of violence against victim
Threats to inform family, community or public
Violence on family (threats or effective)
Withholding of money
Recruitment by abuse of vulnerability Medium indicators Abuse of difficult family situation
Abuse of illegal status
Abuse of lack of education
Abuse of lack of information
Control of exploiters
Economic reasons
False information about law, attitude of authorities
False information about successful migration
Family situation
Personal situation
Psychological and emotional dependency
Relationship with authorities/legal status
Weak indicators Abuse of cultural/religious beliefs
General context
Difficulties in the past
Difficulty to organise travel
Exploitation Strong indicator Excessive working days or hours
Medium indicators Bad living conditions
Hazardous work
Low or no salary
No respect of labour laws or contract signed
No social protection
Very bad working conditions
Wage manipulation
Weak indicators No access to education
Coercion at destination Strong indicators Confiscation of documents
Debt bondage
Isolation, confinement or surveillance
Violence on victims
Medium indicators Forced into illicit/criminal activities
Forced tasks or clients
Forced to act against peers
Forced to lie to authorities, family etc
Threat of denunciation to authorities
Threat to impose even worse working conditions
Threats of violence against victim
Under strong influence
Violence on family (threats or effective)
Withholding of wages
Weak indicator Threats to inform family, community or public
Abuse of vulnerability at destination Medium indicators Dependency on exploiters
Difficulty to live in an unknown area
Economic reasons
Family situation
Relationship with authorities/legal status
Weak indicators Difficulties in the past
Personal characteristics

Source: ILO 2009

More recently, ILO (2012) developed survey guidelines for estimating the incidence of forced labour among adults and children. The guidelines describe the four dimensions of forced labour as (ILO 2012: 14–15):

  • unfree (forced or deceptive) recruitment;
  • work and life under duress (ie the experience of ‘adverse work or living situations imposed upon a person by the use of force, penalty or menace of penalty’);
  • impossibility of leaving the employer; and
  • penalty or menace of penalty (or means of coercion applied to the victim and or their family, including threat and violence, restriction of freedom of movement, debt bondage, withholding wages, retention of passport and abuse of vulnerability).

The indicators are categorised to represent the three phases (or first 3 dimensions outlined above) through which a trafficker may coerce a victim. As for the ILO trafficking indicators, indicators of forced labour are ranked according to their ‘strength’ of relationship—in this case to involuntariness and penalty. An example of indicators measuring ‘impossibility of leaving the employer’ for adult victims of forced labour is given in Table 8.

Table 8 ILO indicators of forced labour for adults: Impossibility of leaving the employer
Indicators of involuntariness
Indicator strength Indicator
Strong indicator Reduced freedom to terminate labour contract after training or other benefit paid by employer
No freedom to resign in accordance with legal requirements
Forced to stay longer than agreed while waiting for wages due
Forced to work for indeterminate period in order to repay outstanding debt or wage advance
Indicators of penalty
Indicator strength Indicator
Strong indicator Denunciation to authorities
Confiscation of identity papers or travel documents
Imposition of worse working conditions
Locked in work or living quarters
Sexual violence
Physical violence
Other forms of punishment (eg deprivation of food, water, sleep)
Removal of rights or benefits
Religious retribution
Under constant surveillance
Violence imposed on other workers in front of all workers
Withholding of assets (cash or other)
Withholding of wages
Threats against family members
Medium indicator Dismissal
Exclusion from future employment
Exclusion from community and social life
Extra work for breaching labour discipline
Financial penalties
Informing family, community or public about worker’s current situation (blackmail)

Source: ILO 2012

US Department of Justice’s Human Trafficking Reporting System

The Human Trafficking Reporting System (HTRS) is an incident-based collection system, which collects data on human trafficking cases investigated by Bureau of Justice Assistance-funded human trafficking task forces (Kyckelhahn, Beck & Cohen 2009). The HTRS was developed to meet a stipulation under the Trafficking Victims Protection Reauthorization Act of 2005 that there be ‘biennial reporting on the scope and characteristics of human trafficking in the United States, using available data from state and local authorities’ (Banks & Kyckelhahn 2011: 2). For the purposes of the HTRS, human trafficking is defined as:

the recruitment, harbouring, transportation, provision or obtaining of a person for one of three purposes: labor or services, through the use of force, fraud, or coercion for the purposes of subjection to involuntary servitude, peonage, debt bondage, or slavery; a commercial sex act through the use of force, fraud, or coercion; any commercial sex act, if the person is under 18 years of age, regardless of whether any form of coercion is involved (Kyckelhahn, Beck & Cohen 2009: 14).

Data has been collected on human trafficking incidents, arrests, prosecutions and imprisonment since 2008, where an incident is defined as:

…any investigation into a claim of human trafficking, or any investigation of other crimes in which elements of potential human trafficking were identified (Banks & Kyckelhahn 2011: 2).

All incidents are retained in the HTRS, irrespective of whether they are ultimately substantiated as a case of human trafficking. Two reports have been published using HTRS data (see Banks & Kyckelhahn 2011; Kyckelhahn, Beck & Cohen 2009). Table 9 lists the data items from the HTRS described in these reports.

Table 9 Key data items in the Human Trafficking Reporting System
Theme Data items
Incident Status (open/closed)
Type of human trafficking (sex trafficking, labour trafficking, other, unknown)
Lead investigating agency (law enforcement, victim advocacy, human services, regulatory agency, unknown)
Number of known victims
Type of location
Confirmed case (yes/no/pending)
Number of known suspects
Victims Gender
Age
Citizenship (US citizen, US national, permanent resident, undocumented alien, qualified alien)
Race/Hispanic origin
Suspects Gender
Age
Citizenship
Race/Hispanic origin
Type of arrest (federal/state)
Charges filed
Current status of case

Source: Banks & Kyckelhahn 2011; Kyckelhahn, Beck & Cohen 2009

IRCP SIAMSECT and MONTRASEC Projects

The SIAMSECT and MONTRASEC projects represent two stages of development work to improve the collection of ‘reliable and comparable…indicators and other relevant data’ by European Union countries on missing and sexually exploited children, and trafficking in human beings (Vermeulen & Paterson 2010: 14). The SIAMSECT project, undertaken by the IRCP in collaboration with the Joint Research Centre on Transnational Crime (Transcrime), explored the definitions and range of data items for inclusion in standardised, interlinked templates to collect data on trafficking, sexually exploited children and missing children. Two of the objectives for designing the templates were to produce comparable data and promote ‘communication and cooperation’ between reporting entities and Member States (Vermeulen & Paterson 2010: 15). The MONTRASEC project involved the development of an IT tool that could be used by law enforcement, criminal justice, non-government, and social and labour inspection agencies to record information on cases of missing or sexually exploited children, or human trafficking. It also involved the development of a report sheet that could be used by National Rapporteurs’ for Trafficking in Human Beings, and formed the basis of intercountry comparison of the nature and extent of human trafficking across the European Union. Data items included in entry forms for recording cases of human trafficking are shown in Table 10.

Table 10 Key data items in the Human Trafficking Reporting System cont.
Events Data items
Activities
Recruitment
Transportation
Transfer
Harbouring
Receipt of persons
Recruitment
Date Period of the event
Manner of initiation of contact Personal contact
Newspaper advertisement
Radio advertisement
Internet advertisement
Television advertisement
Sold by family member
Kidnapped
Other
Transportation and transfer
Duration of transportation Duration
Means of transport used Includes car, bus, train, boat, airplane
Nations crossed Country of origin
Country(s) transited
Country of transition
Borders crossed Green border/Blue border/unknown
Exploitation in the transportation Exploitation during transportation
Type of exploitation Type of exploitation (includes sexual/labour/other)
Harbouring and receipt
Place(s) of harbouring Includes apartment/private dwelling, hotel/motel, camping area, place of exploitation
Exploitation
Duration of exploitation Duration
Sexual exploitation Experienced sexual exploitation
Type of sexual exploitation Includes prostitution, child prostitution, pornography, sex tourism, other
Place of sexual exploitation Includes outdoor, indoor (apartment, brothel, sauna, club, hotel/motel, pub/bar), call girls/escort service, other
Labour exploitation Experienced labour exploitation
Type of labour exploitation Includes slavery, compulsory work, bonded labour
Sector of labour exploitation Includes agriculture, industry, commerce, services, private, leisure
Other forms of exploitation Other forms of exploitation
Type of other exploitation Includes begging, low-level criminality, street selling, removal of organs, military service, illegal adoption, other
General characteristics of the event
Modus operandi Misuse of position or of position of vulnerability
Administration of drug/medication
Abduction
Restrictions on freedom of movement allowed
Takes documents away from victim
By means of deception
Promise of marriage/engagement
By means of force/threat or other forms of coercion
Through debt bondage
Giving or receiving payments or benefits to achieve the consent of a person having control over another person
Continuous control over the victim
Agreement with the author
Sale of person into ownership of another
Other
Victim Data item
Personal data Name/alias/nickname
Sex
Date of birth
Country of birth
Place of birth
Nationality
Fingerprints
Criminal record
Marital status
Structure of the family or origin
Number of children
Education
Status towards immigration legislation (includes residence permit, asylum seeker, refugee, irregular migrant, tourist)
Information on the pre-departure situation
Living situation Person victim was living with
Country or residence Country of residence
Place of residence Place of residence
Income Occupation
Economic status Victim’s perception of economic status
Motives to migrate Improve economic status
Searching a better future
Political instability in country of origin
Personal relationship with recruiter
Other
Information on transport/exploitation
Liaison between victim(s) and author(s) Identity of liaison
Role or profession of victim Sexual exploitation (eg escort/call girl)
Labour exploitation (eg au pair/construction sector/employee in textile sector)
Other forms
Transportation/exploitation
Money requested/paid Victim is ‘sold’
Price paid for victim
Victim’s debt towards authors
Personal documents Seizure of documents at arrival (yes/no)
Includes work permit, identity card, passport, driving licence, visa, birth certificate, marriage certificate, residence permit, other, no documents used
Use of forged documents
Includes work permit, identity card, passport, driving licence, visa, birth certificate, marriage certificate, residence permit, other, no documents used
Revictimisation Revictimised (yes/no)
Revictimised—same crime (yes/no)
Revictimised—same area of exploitation
Area of exploitation
Average income from exploitation Average daily income from sexual exploitation
Average income from other forms of exploitation
Average monthly income from labour exploitation
Income received for removal of organs/illegal adoption
Background of victim’s clients Includes local, internationals, military, police, civilians
Assistance to victims
First assistance referral Includes police, judicial office, NGO, government organisation, hospital or medical facilities, individual, hotline, outreach services, other
Institution providing assistance Institution type
Kind of assistance provided Includes self-employment, vocational training, grant scheme, micro-credit, job referral subsidised employment, education, legal counselling, medical referral or assistance, temporary residence permit, covering documents, family support, housing, shelter
Assistance provided for return to origin country Includes temporary safe accommodation, facilitation of visa/travel documents, travel arrangements, disbursement of travel/reinstallation grant, risk assessment on country of origin, securing of temporary documents
Place the victim can go (includes family, friends, partner, NGO, government organisation, alone, no place)
Means of supporting (includes family, job, NGO, government organisation, no support)
Intention of the victim upon return Intention (includes return to school, return to previous job, find another job, find a legal job, abroad, travel abroad, unknown)
Author Data item
Personal data Name/alias/nickname
Sex
Date of birth
Country of birth
Place of birth
Nationality
Country of residence
Place of residence
Fingerprints
Criminal record
Record for trafficking
Marital status
Education
Income Occupation
Status towards immigration legislation
Information on transport/exploitation process
Organised criminal group Part of organised criminal group
Number of members in group
Role in group (includes head, active member, external cooperator)
Role in commission of event Includes recruiter, passeur, driver, premises owner, photographer, impresario, pimp, door waiter, movie director, entrepreneur, contractor, middleman, other
Relationship author-victim Transporter is also final exploiter
Number of victims had contact with
Fellow citizen with majority of victims

Source: Adapted from Vermeulen & Paterson 2010

UNODC Global report on trafficking in persons

UNODC has prepared three global reports on human trafficking. The first report, which includes data from 155 countries covering the period 2003–07, was developed from a global data collection exercise, commenced under the framework of the United Nations Global Initiative to Fight Human Trafficking (UNODC 2009). The purpose of this data collection was to provide a ‘systematic global mapping of the existing official data’, allowing the international community access to a repository of current data and an overview of the state of the world’s response to human trafficking (Lemay 2008: 3). Data were collected on the status of legislative and administrative frameworks, criminal justice responses (including number of investigations, arrests, prosecutions and convictions) and victim services (number of victims identified by authorities and number of victims given shelter by relevant service providers).

The second report, presenting data from 132 countries mostly for the period 2007–10, is the first in a biennial series on the global, regional and national ‘manifestation’ of human trafficking, and responses to trafficking (UNODC 2012). This series followed the UN General Assembly’s adoption in 2010 of the UN Global Plan of Action to Combat Trafficking in Persons and a request from the General Assembly that the UNODC undertake regular data collection and reporting on human trafficking.

Information was sourced from government and non-government organisations. The 2012 report differed from the 2009 report by collating data from a questionnaire distributed to government agencies and using results from the UN Survey of Crime Trends and Operations of Criminal Justice Systems (see UNODC 2013), as well as obtaining publicly available information recorded by government and non-government entities. Topics described in one or both of these reports include:

  • gender, age and nationality of victims;
  • type of exploitation;
  • gender and nationality of offender;
  • incidence of domestic, regional and transnational trafficking;
  • number and rate of convictions; and
  • proportion of states with full, partial or no legislation criminalising human trafficking.

The third report followed the methodology of the second, collecting information on the above variables through the completion of a questionnaire by government agencies and the collation of official, publicy available information from government, non-government and international organisations (UNODC 2014). A total of 128 countries contributed to the report and it included reference to human trafficking and slavery cases prosecuted in 2011 and 2012, as well as qualitative description of five cases for each country represented.

National Rapporteur on Trafficking in Human Beings (the Netherlands)

The Bureau of the National Rapporteur on Trafficking in Human Beings, which comprises the National Rapporteur on Trafficking in Human Beings and Sexual Violence Against Children, is the national coordinator of data collected on human trafficking and sexual violence against children in the Netherlands. Information specifically on human trafficking is compiled in annual reports, which are presented to the Minister of Justice. Nine reports have been published since 2002. The annual reports describe:

the nature and scale of human trafficking, the mechanisms that play a role in human trafficking, the developments taking place in this field, and the effects of relevant policy (National Rapporteur on Trafficking in Human Beings 2010: 11).

Data are collected on victims from three primary sources—CoMensha (the national reporting and registration point for victims of human trafficking), the Immigration and Naturalisation Service (for data on victims applying and granted residence permits) and the Central Fines Collection Agency (for data on orders to pay compensation to victims). The Public Prosecution Service provides data on suspects and offenders. The data items presented in the ninth annual report are shown in Table 11.

Table 11 Data included in reports prepared by the National Rapporteur on Trafficking in Human Beings and Sexual Violence Against Children (the Netherlands)
Theme Indicator
Victim Gender
Age
Nationality
Sector of exploitation
Source of referral (‘notifier’)
Purpose of notification
B9 visas Visa applications
Visas granted
Grantee—age, gender, nationality, region of origin
Compensation Compensation orders
Amount awarded
Disposition method
Suspect/offenders Gender
Age
Country of birth
Number of cases registered
Nature of offences recorded
Most serious offence
Detained in preventive custody
Cases dealt with—first instance/on appeal
Disposition
Nature of conviction
Sentence imposed
Length of sentence
Appeal filed

Source: National Rapporteur on Trafficking in Human Beings 2013, 2010

Bundeskriminalamt: Trafficking in human beings national situation reports

Bundeskriminalamt, the German Federal Criminal Police Office, collates data on all police investigations into suspected cases of human trafficking with reference to offences under ss 180b and 181 of the German Penal Code (trafficking in human beings and aggravated trafficking in human beings respectively). The results are published in the national situation reports on Trafficking in Human Beings, with the objective of assisting police and government to assess ‘the threat and damage potential(ly) inherent in human trafficking as well as its significance’ and the responses required (BKA 2007: 1). Seven reports summarising this data have been released, covering the periods 2002, 2004 and 2006–10. The comparability of the data between the first two and five latter years of reporting is limited due to an expansion of the offence of trafficking in human beings from sexual exploitation to include the exploitation of workers and a change in counting rules where only investigations concluded during the reporting period are considered. The most recent report (BKA 2010) contained data on the following variables (see Table 12).

Table 12 Data variables reported in the Bundeskriminalamt’s Trafficking in Human Beings national situation reports
Theme Indicator
Investigation Location of investigation (federal states)
Other offences identified during investigation
Trigger for investigation
Manner of first contact between police and victim
Police activities prior to initiation of investigation
Suspect Gender
Nationality (current/at birth)
Number per investigation
Victim Type of exploitation (sexual/worker)
Gender
Age
Nationality
Immigration status
Recruitment method(s)
Location of exploitation
Receipt of counselling support
Circumstances of prostitution (if trafficked for sexual exploitation)

Source: BKA 2010

European Commission: EUROSTAT trafficking in human beings

The Trafficking in Human Beings report, prepared by EUROSTAT, is the first published EU-wide examination of human trafficking (Eurostat 2013). The report includes data from the 27 EU Member States, plus Iceland, Norway, Switzerland, Croatia, Montenegro, Serbia and Turkey. These data were collected using a specially developed data collection tool that listed indicators and variables, definitions of key terms (eg identified versus presumed victim, child victim, recruitment) and guidelines for populating the indicator tables. Information was sourced from law enforcement, criminal justice agencies, immigration services, labour inspectorates and non-government organisations. Indicators are grouped into four categories—information on victims, police data on suspected traffickers, data on prosecuted traffickers and court data on convicted traffickers (see Table 13).

Table 13 EUROSTAT trafficking in human beings indicators
Theme Indicator
Victim Number by registering organisation
(Identified and presumed) Gender
Age
Form of exploitation
Citizenship
Internal (within EU) trafficking
Domestic trafficking
Received assistance and protection
Provided with reflection period
Given residence permit
Suspected traffickers Gender
Citizenship
Internal trafficking
Same citizenship as registering country
Form of exploitation
Prosecuted traffickers Gender
Citizenship
Form of exploitation
Final decisions by prosecution service
Convicted traffickers Gender
Form of exploitation

Source: Eurostat 2013

UNODC Case law database

The UNODC’s online Case Law Database includes information on prosecuted cases of human trafficking and slavery (among other crimes) from around the world. The cases are provided voluntarily by government and international agencies, and are not necessarily representative of the cases identified or prosecuted in these countries. At the time of writing, it included more than 1,000 cases from 90 countries (UNODC 2015). Categories of information included in case summaries are shown in Table 14.

Table 14 Categories of information for human trafficking and slavery cases recorded in the UNODC Case Law Database
Categories Data items (fields)
Case descriptors Acts (recruitment, transportation, receipt, transfer, harbouring)

Means (threat or use of force or other means of coercion, abduction, fraud, deception, abuse of power or a position of vulnerability, giving or receiving payments or benefits to achieve the consent of a person having control over another person)

Form of trafficking (internal, transnational, organised criminal group)

Sector in which exploitation takes place (agriculture, begging, construction, commercial sexual exploitation, domestic servitude, factory/manufacturing, hair/beauty salon, hotel/restaurant/bar, mining, organ/tissue removal, other sectors)
International cooperation (mutual legal assistance, extradition, transfer of sentenced person)
Procedural information Country (in which case was prosecuted)
Sentence date
Legal system (Civil law, Common law, mixed system)
Latest court ruling (Apellate court, Court of 1st instance, High court, International court/Treaty body, Supreme court)
Type of court/tribunal (Administrative, Civil, Criminal, Labour)
Defendant information Nationality
Age
Gender (male, female)
Verdict (Guilty, not guilty, withdrawn, other)
Charge/claim
Legislation/statute/code
Legal reasoning
Apellate decision (remanded, upheld, reversed)
Term of imprisonment
Victim information Nationality
Gender/minor status
Age

Source: http://www.unodc.org/cld/index-sherloc-cld.jspx?

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