HA3018
Human Trafficking:
Beyond the Sex Trade
By Ho Li Vun (Erica), Lim Dallas Shi Yun,
Sarah Shahbal Tan Chin, Soo Hwee Sharon, Yeonju Kang
Overview
01
Reading #1 Summary
02
Reading #2 Summary
Measuring the Nature and
Prevalence of Human
Trafficking (2020)
Amy Farrell and Ieke de
Vries
The Slave Next Door, Chap 2:
House Slaves
Bales and Soodalter
03
Trafficking or Not?
04
Concluding Thoughts
Case Study in Singapore
Activity and Discussion
A short recap & Other
considerations
01
Reading #1 Summary
Measuring the Nature and Prevalence
of Human Trafficking (2020)
Amy Farrell and Ieke de Vries
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Difficulties in measuring human trafficking victimisation
due to:
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data constraints
definitional limitations
victims’ perspective
detection problems
Mainly, 4 methodologies have been outlined:
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Capture-Recapture Approach
Multiple System Estimation (MSE)
Local Surveys and Field Observations
Online Domain Data and Network Information
Importance of Data
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Data allows us to understand the magnitude of the problem
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who is at risk of trafficking
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the social conditions that breed trafficking crimes.
Accurate data allows us to design more targeted and effective
responses
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Challenge: data is fixated on the number of victims rather than the
data of perpetrators and the nature of criminal organisations who
traffick humans.
Difficulties in Measuring Trafficking Victimisation
Definitional Limitations
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Definitions are not universally agreed upon.
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The range of activities counted as human trafficking is contextual.
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Accurate measurements require precision in identifying the objects
being counted.
Victims do not recognise themselves as victims
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The public generally lacks information about human trafficking
victimisation.
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A victim may not realised that they were exploited.
Undetected Victims
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Perpetrators deliberately hide victims.
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Victims do not commonly seek help.
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Victims may fear the repercussions of being reported to the police.
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The police officials could be part of the human trafficking network.
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Victims may be traumatised.
Officials may not be able to recognise a human trafficking victim when they
come across one
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Lack of knowledge
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Lack of procedures put in place such as screening tools and training
Method 1: Capture-Recapture Approach via Open Source Info
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Estimate populations by taking independent
samples of a population, and identifying
likelihood of re-identification when the
population is re-sampled
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By estimating the rough percentage that is
never caught, derive the full number
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Used by social scientists to study hidden
people/groups
Method 1: Capture-Recapture Approach via Open Source Info
Assumptions Made
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The population being studied is constant
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Subjects have equal chances of being captured each time
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The chances of being captured the second time must be independent of
the first time
Limitations
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Data quality
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Consistency
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Difficulty in obtaining identifying information of individuals in hidden
populations
Method 2: Multiple System Estimation via Admin. Records
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MSE is similar to the capture-recapture method, but uses
administrative data from multiple sources instead of open sourced data
to predict population sizes.
Limitations
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Lack of data in many communities
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Officials may not accurately report information
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Confidentiality concerns
Method 3: Local Surveys & Field Observations
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Captures information directly from people who may have been
affected by human trafficking and populations that are harder to reach.
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Chain referral sampling (snowball sampling) identifies ‘seeds’
who can refer and connect researchers to individuals who have
experiences with human trafficking.
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It is also possible to integrate field survey questions into national public
surveys.
Method 3: Local Surveys & Field Observations
Limitations
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Time and resource intensive
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Even if victims are disclosed, they may not be in a position to disclose
their situations
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they may be constricted by fear, shame and financial necessities
Informants may selectively withhold information
Method 4: Use of Online Domain & Network Approaches
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The internet allows traffickers to access a potentially new field of
distanced victims, clients and other offenders.
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The internet offers a wider array of possibilities to detect crime.
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Machine learning, data mining, information retrieval and information
integration to automatically compile and collect information from
internet sources.
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Network analysis allows us to expose the structure and interactions
within the human trafficking networks, the flow of goods, money and
information.
Moving Forward
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The importance of committing and be committed to improve
administration data
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Funding is needed to support labour and time intensive studies
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New sources of data needs to be continually explored
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Collaboration is key
02
Reading #2 Summary
The Slave Next Door, Chap 2: House Slaves
Bales and Soodalter
Key Points
Desire & Ability
to Escape
Understanding
the Trafficker
Failure of Policy
& Legislation
Stakeholders in
the Ecosystem
Desire & Ability to Escape
While at home
● Manipulation
○ The house as the only safe space (p. 22) → discourages her from leaving
○ Internalised immorality - ‘her enslavement is her own fault’ (p. 23)
○ Aided by her food & rest intake - keeps her confused & obedient (p. 24)
● Emotional attachment to the employer’s children
○ She doesn’t want to leave them unprotected with her employer (p. 24)
Desire & Ability to Escape
Escaping the home
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Fear of repercussion
○ Threats to loved ones, murder → ‘many victims, even when given the
chance, do not testify’ (p. 21)
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Language and geographical isolation
○ Struggles to seek help
○ Loses her identity & ability to speak for herself (p. 23)
Understanding the Trafficker
Hunger for power perpetuates the domestic slave trade
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As opposed to profit (which is the main cause of other forms of HT)
○ ‘The families that hold and abuse domestic slaves can afford to pay for the same
services in the normal way. For this kind of slavery, at least, the allure is power
itself’ (p. 30)
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He desires absolute power because it is addictive and/or because he feels powerless
in all other areas
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Exercising superiority
○ Attempts to use stress from personal life, racial & ethnic differences, and moral
leadership to justify this action
Failure of Policy & Legislation
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Employers often enjoy stronger legal protection
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Her visa is tied to her employer without further assessment
○ ‘To get the visa, the employer just has to state that he will provide
‘reasonable living and working conditions’ (p. 35)
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Lack of standardised, inclusive definitions of household workers leaves
these women unprotected
○ ‘The National Labor Relations Act doesn’t include household workers
in its definition of ‘employees’’ (pg. 22)
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Unfair charges against convicted slaveholders
○ ‘psychological coercion is extremely hard to prove’ (pg. 31)
Stakeholders in the Ecosystem
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Au pairs
○ Have a network of friends; required to be paid at least the minimum
wage; not allowed to work >45 hrs a week; must have a private
bedroom; employers are assessed for suitability (pg. 36)
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Calls for ordinary citizens to be good samaritans
03
Singapore’s Domestic Worker
Sector: Trafficking or Not?
https://www.youtube.com/watch?v=Sj-vHlHEgtM&ab_channel=CNA
Video Summary + Case Study
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The ban from Myanmar was put in place due to concerns over domestic
worker abuse, especially in Singapore (and other parts of South Asia).
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Singapore continued to issue visas to domestic workers coming from Myanmar,
and did not respond to Myanmar’s requests to sign a memorandum of
understanding on the issue.
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Myanmar wants to protect their workers, but Singapore feels that workers with
valid work permits are welcome to stay. This creates a grey area.
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Debt bondage
Singapore’s Labour Laws
Employment of Foreign
Manpower Act (EFMA)
Employment Act (EA)
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No more than 12 hour work days
No more than 72 hours overtime per month
General guidelines for overtime, rest day and
public holiday pay
Minimum standards on
○ notice periods,
○ annual leave and paid sick
○ and hospitalization leave.
Excludes domestic workers as it is “quite
different from normal work”
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No legal limits on working hours
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Ambitious language impacting MDW welfare
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‘acceptable’ accommodation,
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‘adequate’ food,
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‘adequate’ rest,
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and ‘reasonable’ notice of repatriation
Inconsistent enforcement
Food for Thought!
1.
1.
Is this considered human trafficking? Is the definition of human
trafficking adequate in capturing the extent of this problem?
List some reasons why Singapore would continue issuing permits to
domestic workers arriving from Myanmar. Was it ethical for them to
allow migrants from Myanmar without tightening laws in place to
protect domestic workers?
You may want to consider political, economic, socio-cultural and legal forces at play
“Human Trafficking is the
recruitment,
transportation, transfer,
harbouring or receipt of
people through force,
fraud or deception, with
the aim of exploiting
them for profit.”
(UN Office of Drug and Crime)
1.
In hindsight, was the ban on domestic worker migration justified in
the attempt to protect its people or did it end up limiting
opportunities for women instead?
04
Concluding Thoughts
A Short Recap
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The importance of data accumulation and, what type of data is missing from the
narrative & how data might be more accurately captured
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The layers of psychological, systemic, and institutional barriers of why trafficking
is so difficult to escape from
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Potential issues with the definition of human trafficking
Other Considerations
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Beyond the sector of domestic work, what other areas are trafficked persons forced
(or led) to?
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What can we do?