Global Slavery Index
The Global Slavery Index is an annual ranking of slavery conditions in countries (2013 n = 162, 2014 n = 167) world wide published by the Walk Free Foundation.[1] In 2013, the first Global Slavery Index included information about (1) prevalence (2) vulnerability and (3) country level national responses. In 2013 the Index itself is calculated based on a combined measure of three factors: 1) estimated prevalence of modern slavery by population (using primary and secondary data sources); 2) a measure of child marriage; and 3) a measure of human trafficking in and out of a country.
In 2014, the methodology was substantially updated.[2] The 2014 Global Slavery Index includes 3 data points for each country, on (1) national estimates of prevalence of modern slavery (2) vulnerability measures (3) assessment of strength of government responses.[3] The Index has been pioneering the use of random-sampled, nationally representative surveys to estimate prevalence at the national level. This included commissioning 7 such surveys in 2014; and a further 19 surveys through Gallup World Poll in 2015.[4]
The 2014 Index includes country studies with policy recommendations for many countries including: Australia, Pakistan, India, Brazil, the United Kingdom, the United States, Qatar, and others.
Contents
Calculation[edit]
The 2014 Global Slavery Index includes data on 3 key variables: (1) prevalence of modern slavery in each country (2) vulnerability and (3) government responses to modern slavery. The methodology is written up in detail in a methodology paper.
The first of these factors, the prevalence estimates were derived, using a statistical process known as extrapolation. In 2015, Joudo Larsen, Bales and Datta published an article that describes the extrapolation process, and provides a test of it. Writing in Significance, the magazine of the UK Royal Statistics Society, Joudo Larson et al note that extrapolation in the 2014 Global Slavery Index involved several steps:
- Clustering: Countries were grouped into 7 clusters, based on an analysis of how similar or different they are, when factors relevant to vulnerability of enslavement are taken into account. The data on vulnerability included variables on five dimensions: state stability, social discrimination, presence or absence of human rights protections, economic and social development, and presence of governmental slavery policy. The groups were chosen by a K-means clustering algorithm, deciding on the final cluster out of a dozen trials that had the highest pseudo-F score. Seven groups were chosen as there were seven prevalence surveys that used the same instruments and data collection methods, and ideally, each survey could be applied to a unique group.
- Extrapolation: survey data on prevalence that was available for each cluster (expressed as a percentage of the population) was then used as the basis of the estimation for other countries within that same cluster. A slightly different method was followed for 'cluster 1', which involved mostly European and highly developed countries. This is discussed further below in the article by Bales and Datta,[5]
- National level adjustments were done by hand on a country by country basis, reflecting considerations such as geography.
This resulted in a prevalence estimate for each country calculated as a proportion of the total population that was enslaved within that country. For all 167 countries this produced a total global estimate in 2014 of 35.8 million enslaved people.
Writing in 2015, Larsen et al note that newer 2015 survey estimates now allow a comparison and test of at least some of the 2014 extrapolated estimates. This is important for checking the validity of the earlier results and the continued application and use of this methodology. The comparisons suggest that extrapolation, while not perfect, is a useful and valid method - as all but one of the extrapolation estimates of prevalence of slavery (considered as a percentage within a national population) fall within one percentage point of the estimates arrived through random sample surveys [6]
Data from the Global Slavery Index is used in the Ibrahim Index of African Governance data portal (http://www.moibrahimfoundation.org/iiag/data-portal/)
In their article "Slavery in Europe: Part 1, Estimating the Dark Figure", Monti Datta and Kevin Bales demonstrate the statistical techniques applied to the estimation of the dark figure of the prevalence of modern slavery across Europe.[5] These same techniques are applied to a dataset that includes random survey sampling (where possible), secondary source estimates, a process of extrapolation, and a country level adjustment to determine the prevalence of people in modern slavery around the world in the Global Slavery Index.[7]
Controversy[edit]
The Global Slavery Index appears to be highly controversial. According to researchers Andrew Guth, Robyn Anderson, Kasey Kinnard and Hang Tran, an analysis of the Index's methods reveals significant and critical weaknesses and raises questions about its replicability and validity. Moreover, the publicity given to the Index is leading to the use of its poor data not only by popular culture and reputable magazines and news outlets but also by academic journals and top policy makers.[8]
Moreover, some countries, for which no data were available, were given the same rate as countries which were judged to be similar. For example, prevalence rates for Britain were applied to Ireland and Iceland and those for America, to several western European nations, including Germany. This aspect of the methodology, known as extrapolation, has attracted some criticism too.[9]
Global Slavery Index 2014[edit]
Vulnerability data | Prevalence data | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Rank | Country | Region | Slavery policy | Human rights | Development | State stability | Discrimination | Mean | Pop. in slavery % | Pop. in slavery n | Population |
1 | Mauritania | Sub-Saharan Africa | 92.9 | 75.3 | 76.8 | 62.7 | 67.6 | 72.2 | 4.0000 | 155,600 | 3,889,880 |
2 | Uzbekistan | Russia and Eurasia | 54.0 | 91.8 | 39.0 | 62.8 | 38.6 | 56.5 | 3.9729 | 1,201,400 | 30,241,100 |
3 | Haiti | Americas | 68.2 | 67.0 | 81.3 | 64.3 | 75.0 | 71.9 | 2.3041 | 237,700 | 10,317,461 |
4 | Qatar | Middle East and North Africa | 50.5 | 82.3 | 28.1 | 26.1 | 70.1 | 50.8 | 1.3563 | 29,400 | 2,168,673 |
5 | India | Asia Pacific | 85.9 | 58.9 | 54.0 | 56.5 | 38.3 | 56.7 | 1.1409 | 14,285,700 | 1,252,139,596 |
6 | Pakistan | Asia Pacific | 85.9 | 79.2 | 60.4 | 68.9 | 60.0 | 69.5 | 1.1300 | 2,058,200 | 182,142,594 |
7 | Democratic Republic of the Congo | Sub-Saharan Africa | 78.8 | 78.0 | 83.9 | 80.7 | 64.3 | 79.3 | 1.1300 | 762,900 | 67,513,677 |
8 | Sudan | Sub-Saharan Africa | 78.8 | 100.0 | 79.7 | 79.8 | 59.9 | 82.6 | 1.1300 | 429,000 | 37,964,306 |
9 | Syria | Middle East and North Africa | 100.0 | 100.0 | 55.3 | 74.7 | 54.1 | 76.9 | 1.1300 | 258,200 | 22,845,550 |
10 | Central African Republic | Sub-Saharan Africa | 92.9 | 83.5 | 82.3 | 77.0 | 66.2 | 78.9 | 1.1300 | 52,200 | 4,616,417 |
11 | Republic of the Congo | Sub-Saharan Africa | 64.6 | 50.5 | 69.6 | 57.3 | 69.4 | 61.7 | 1.1061 | 49,200 | 4,447,632 |
12 | United Arab Emirates | Middle East and North Africa | 39.9 | 85.0 | 34.4 | 34.1 | 40.6 | 46.8 | 1.0572 | 98,800 | 9,346,129 |
13 | Iraq | Middle East and North Africa | 71.7 | 91.8 | 61.3 | 77.2 | 59.0 | 71.7 | 1.0351 | 345,900 | 33,417,476 |
14 | Cambodia | Asia Pacific | 75.3 | 58.8 | 54.8 | 65.3 | 63.6 | 62.9 | 1.0292 | 155,800 | 15,135,169 |
15 | Moldova | Russia and Eurasia | 4.5 | 58.0 | 40.1 | 52.6 | 53.6 | 41.8 | 0.9362 | 33,300 | 3,559,000 |
16 | Mongolia | Asia Pacific | 64.6 | 28.5 | 35.7 | 42.5 | 44.9 | 44.0 | 0.9068 | 25,700 | 2,839,073 |
17 | Namibia | Sub-Saharan Africa | 78.8 | 23.0 | 49.6 | 35.7 | 72.5 | 51.2 | 0.9068 | 20,900 | 2,303,315 |
18 | Botswana | Sub-Saharan Africa | 85.9 | 35.5 | 50.2 | 29.6 | 53.6 | 51.8 | 0.9068 | 18,300 | 2,021,144 |
19 | Suriname | Americas | 47.0 | 23.0 | 53.3 | 35.7 | 63.4 | 45.2 | 0.9068 | 4,900 | 539,276 |
20 | Nepal | Asia Pacific | 61.1 | 61.7 | 64.9 | 50.7 | 30.1 | 53.2 | 0.8227 | 228,700 | 27,797,457 |
21 | Ghana | Sub-Saharan Africa | 71.7 | 25.9 | 67.9 | 46.2 | 63.5 | 54.4 | 0.7456 | 193,100 | 25,904,598 |
22 | Mozambique | Sub-Saharan Africa | 54.0 | 44.9 | 77.8 | 55.5 | 41.0 | 55.5 | 0.7456 | 192,600 | 25,833,752 |
23 | Niger | Sub-Saharan Africa | 61.1 | 47.8 | 86.9 | 55.2 | 50.2 | 60.2 | 0.7456 | 132,900 | 17,831,270 |
24 | Burkina Faso | Sub-Saharan Africa | 54.0 | 38.8 | 83.7 | 58.9 | 42.8 | 55.8 | 0.7456 | 126,300 | 16,934,839 |
25 | Malawi | Sub-Saharan Africa | 64.6 | 43.5 | 89.1 | 41.6 | 57.9 | 58.6 | 0.7456 | 122,000 | 16,362,567 |
26 | Zambia | Sub-Saharan Africa | 61.1 | 51.1 | 71.4 | 48.5 | 67.7 | 58.9 | 0.7456 | 108,400 | 14,538,640 |
27 | Senegal | Sub-Saharan Africa | 43.4 | 38.1 | 76.4 | 54.3 | 55.7 | 55.7 | 0.7456 | 105,400 | 14,133,280 |
28 | Benin | Sub-Saharan Africa | 61.1 | 36.7 | 80.3 | 51.0 | 50.1 | 56.7 | 0.7456 | 77,000 | 10,323,474 |
29 | Togo | Sub-Saharan Africa | 68.2 | 50.5 | 76.9 | 60.4 | 48.1 | 60.1 | 0.7456 | 50,800 | 6,816,982 |
30 | Liberia | Sub-Saharan Africa | 78.8 | 35.9 | 81.6 | 53.7 | 52.0 | 59.7 | 0.7456 | 32,000 | 4,294,077 |
31 | Lesotho | Sub-Saharan Africa | 82.3 | 34.0 | 70.4 | 46.0 | 52.1 | 57.7 | 0.7456 | 15,500 | 2,074,465 |
32 | Russia | Russia and Eurasia | 54.0 | 89.9 | 29.7 | 67.0 | 47.5 | 56.2 | 0.7315 | 1,049,700 | 143,499,861 |
33 | Tanzania | Sub-Saharan Africa | 54.0 | 62.9 | 81.6 | 54.9 | 67.5 | 64.2 | 0.7114 | 350,400 | 49,253,126 |
34 | Ivory Coast | Sub-Saharan Africa | 57.6 | 65.6 | 78.5 | 67.6 | 55.7 | 65.0 | 0.7114 | 144,500 | 20,316,086 |
35 | Mali | Sub-Saharan Africa | 92.9 | 41.7 | 81.4 | 64.5 | 45.7 | 64.0 | 0.7114 | 108,900 | 15,301,650 |
36 | Chad | Sub-Saharan Africa | 75.3 | 60.7 | 86.4 | 74.1 | 64.9 | 73.7 | 0.7114 | 91,200 | 12,825,314 |
37 | Rwanda | Sub-Saharan Africa | 75.3 | 71.2 | 70.2 | 45.9 | 54.1 | 63.5 | 0.7114 | 83,800 | 11,776,522 |
38 | Guinea | Sub-Saharan Africa | 71.7 | 64.3 | 82.4 | 69.7 | 61.5 | 70.0 | 0.7114 | 83,600 | 11,745,189 |
39 | South Sudan | Sub-Saharan Africa | 82.3 | 53.3 | 78.5 | 72.5 | 57.3 | 66.7 | 0.7114 | 80,400 | 11,296,173 |
40 | Burundi | Sub-Saharan Africa | 78.8 | 55.2 | 81.9 | 66.4 | 41.7 | 66.3 | 0.7114 | 72,300 | 10,162,532 |
41 | Sierra Leone | Sub-Saharan Africa | 68.2 | 42.0 | 86.0 | 50.7 | 68.2 | 63.0 | 0.7114 | 43,300 | 6,092,075 |
42 | Gambia | Sub-Saharan Africa | 57.6 | 53.3 | 82.5 | 60.6 | 58.8 | 62.5 | 0.7114 | 13,200 | 1,849,285 |
43 | Djibouti | Sub-Saharan Africa | 68.2 | 75.3 | 72.5 | 56.1 | 52.7 | 65.7 | 0.7114 | 6,200 | 872,932 |
44 | Thailand | Asia Pacific | 57.6 | 60.0 | 40.0 | 44.6 | 58.6 | 51.5 | 0.7093 | 475,300 | 67,010,502 |
45 | Oman | Middle East and North Africa | 68.2 | 77.2 | 38.0 | 40.9 | 58.8 | 56.1 | 0.7093 | 25,800 | 3,632,444 |
46 | Kuwait | Middle East and North Africa | 89.4 | 69.9 | 34.3 | 36.8 | 78.2 | 61.8 | 0.7093 | 23,900 | 3,368,572 |
47 | Bahrain | Middle East and North Africa | 78.8 | 86.9 | 27.4 | 37.2 | 56.5 | 58.2 | 0.7093 | 9,400 | 1,332,171 |
48 | Brunei | Asia Pacific | 43.4 | 86.7 | 36.6 | 30.3 | 67.0 | 51.4 | 0.7093 | 3,000 | 417,784 |
49 | Cape Verde | Sub-Saharan Africa | 50.5 | 9.3 | 43.6 | 33.6 | 61.4 | 41.3 | 0.6368 | 3,200 | 498,897 |
50 | Swaziland | Sub-Saharan Africa | 64.6 | 69.5 | 55.2 | 55.8 | 73.2 | 65.0 | 0.5359 | 6,700 | 1,249,514 |
51 | Guinea-Bissau | Sub-Saharan Africa | 92.9 | 50.5 | 82.6 | 72.0 | 60.0 | 70.3 | 0.5001 | 8,500 | 1,704,255 |
52 | Nigeria | Sub-Saharan Africa | 50.5 | 72.7 | 58.5 | 68.4 | 71.0 | 63.6 | 0.4805 | 834,200 | 173,615,345 |
53 | Egypt | Middle East and North Africa | 50.5 | 82.1 | 42.9 | 49.9 | 77.2 | 60.6 | 0.4800 | 393,800 | 82,056,378 |
54 | Algeria | Middle East and North Africa | 89.4 | 92.1 | 49.2 | 48.1 | 48.9 | 64.8 | 0.4800 | 188,200 | 39,208,194 |
55 | Morocco | Middle East and North Africa | 85.9 | 68.9 | 43.9 | 46.6 | 50.9 | 60.0 | 0.4800 | 158,400 | 33,008,150 |
56 | Malaysia | Asia Pacific | 78.8 | 77.4 | 35.6 | 30.4 | 71.5 | 58.1 | 0.4800 | 142,600 | 29,716,965 |
57 | Jordan | Middle East and North Africa | 61.1 | 85.9 | 48.6 | 37.5 | 62.4 | 60.7 | 0.4800 | 31,000 | 6,459,000 |
58 | Lebanon | Middle East and North Africa | 68.2 | 64.8 | 38.2 | 62.5 | 78.4 | 62.5 | 0.4800 | 21,400 | 4,467,390 |
59 | Bangladesh | Asia Pacific | 75.3 | 62.0 | 67.3 | 58.6 | 30.0 | 57.3 | 0.4348 | 680,900 | 156,594,962 |
60 | Iran | Middle East and North Africa | 96.5 | 92.8 | 41.0 | 58.1 | 68.4 | 71.4 | 0.4348 | 336,700 | 77,447,168 |
61 | Myanmar | Asia Pacific | 68.2 | 91.8 | 71.8 | 61.8 | 64.5 | 72.3 | 0.4348 | 231,600 | 53,259,018 |
62 | Afghanistan | Asia Pacific | 78.8 | 69.8 | 91.9 | 79.3 | 54.4 | 75.1 | 0.4348 | 132,800 | 30,551,674 |
63 | North Korea | Asia Pacific | 85.9 | 100.0 | 59.8 | 75.1 | 58.8 | 75.2 | 0.4348 | 108,200 | 24,895,480 |
64 | Yemen | Middle East and North Africa | 89.4 | 94.5 | 64.6 | 69.7 | 84.4 | 80.6 | 0.4348 | 106,100 | 24,407,381 |
65 | Angola | Sub-Saharan Africa | 71.7 | 75.3 | 63.4 | 61.4 | 54.4 | 65.3 | 0.4348 | 93,400 | 21,471,618 |
66 | Zimbabwe | Sub-Saharan Africa | 85.9 | 91.8 | 63.9 | 70.9 | 53.5 | 73.5 | 0.4348 | 61,500 | 14,149,648 |
67 | Somalia | Sub-Saharan Africa | 85.9 | 100.0 | 92.8 | 85.5 | 100.0 | 94.9 | 0.4348 | 45,600 | 10,495,583 |
68 | Eritrea | Sub-Saharan Africa | 92.9 | 100.0 | 86.3 | 55.9 | 83.5 | 83.8 | 0.4348 | 27,500 | 6,333,135 |
69 | Libya | Middle East and North Africa | 89.4 | 88.2 | 50.0 | 63.0 | 83.5 | 75.6 | 0.4348 | 27,000 | 6,201,521 |
70 | Equatorial Guinea | Sub-Saharan Africa | 92.9 | 83.5 | 53.7 | 62.8 | 58.8 | 69.6 | 0.4348 | 3,300 | 757,014 |
71 | Ethiopia | Sub-Saharan Africa | 36.4 | 92.6 | 82.7 | 52.7 | 53.8 | 62.3 | 0.4141 | 389,700 | 94,100,756 |
72 | Guyana | Americas | 71.7 | 39.9 | 68.4 | 49.8 | 67.5 | 57.3 | 0.3870 | 3,100 | 799,613 |
73 | Bulgaria | Europe | 22.2 | 42.4 | 30.9 | 47.9 | 34.1 | 35.5 | 0.3797 | 27,600 | 7,265,115 |
74 | Czech Republic | Europe | 8.1 | 27.9 | 28.7 | 17.7 | 37.6 | 24.0 | 0.3600 | 37,900 | 10,521,468 |
75 | Hungary | Europe | 54.0 | 30.8 | 33.8 | 22.1 | 32.4 | 35.3 | 0.3600 | 35,600 | 9,897,247 |
76 | Serbia | Europe | 25.8 | 45.4 | 34.1 | 43.2 | 40.2 | 37.0 | 0.3600 | 25,800 | 7,163,976 |
77 | Slovakia | Europe | 11.6 | 28.5 | 31.2 | 39.3 | 33.4 | 28.8 | 0.3600 | 19,500 | 5,414,095 |
78 | Georgia | Russia and Eurasia | 57.6 | 71.9 | 37.0 | 45.9 | 46.8 | 51.1 | 0.3600 | 16,100 | 4,476,900 |
79 | Croatia | Europe | 43.4 | 33.8 | 30.8 | 30.3 | 37.0 | 33.7 | 0.3600 | 15,300 | 4,252,700 |
80 | Bosnia and Herzegovina | Europe | 29.3 | 57.2 | 34.9 | 46.4 | 53.8 | 45.7 | 0.3600 | 13,800 | 3,829,307 |
81 | Armenia | Russia and Eurasia | 4.5 | 63.7 | 35.7 | 51.6 | 54.8 | 42.1 | 0.3600 | 10,700 | 2,976,566 |
82 | Lithuania | Europe | 47.0 | 36.4 | 24.5 | 27.1 | 44.3 | 35.2 | 0.3600 | 10,600 | 2,956,121 |
83 | Albania | Europe | 47.0 | 43.6 | 36.0 | 57.0 | 55.3 | 46.3 | 0.3600 | 10,000 | 2,773,620 |
84 | Macedonia | Europe | 25.8 | 41.7 | 33.7 | 54.9 | 46.0 | 39.7 | 0.3600 | 7,600 | 2,107,158 |
85 | Slovenia | Europe | 4.5 | 15.1 | 29.6 | 16.1 | 34.8 | 20.7 | 0.3600 | 7,400 | 2,060,484 |
86 | Estonia | Europe | 50.5 | 13.2 | 28.1 | 24.6 | 43.5 | 30.6 | 0.3600 | 4,800 | 1,324,612 |
87 | Cyprus | Europe | 25.8 | 27.7 | 29.0 | 20.7 | 46.0 | 29.8 | 0.3600 | 4,100 | 1,141,166 |
88 | Montenegro | Europe | 36.4 | 38.8 | 30.3 | 49.5 | 49.0 | 40.8 | 0.3600 | 2,200 | 621,383 |
89 | Vietnam | Asia Pacific | 47.0 | 91.8 | 45.1 | 49.4 | 41.7 | 54.3 | 0.3592 | 322,200 | 89,708,900 |
90 | Uganda | Sub-Saharan Africa | 39.9 | 72.4 | 72.4 | 51.2 | 54.4 | 56.7 | 0.3592 | 135,000 | 37,578,876 |
91 | Cameroon | Sub-Saharan Africa | 32.8 | 71.6 | 74.6 | 59.7 | 57.0 | 58.4 | 0.3592 | 79,900 | 22,253,959 |
92 | Sri Lanka | Asia Pacific | 64.6 | 69.7 | 47.1 | 58.9 | 34.2 | 55.7 | 0.3592 | 73,600 | 20,483,000 |
93 | Kazakhstan | Russia and Eurasia | 36.4 | 75.8 | 34.0 | 57.8 | 38.0 | 49.1 | 0.3592 | 61,200 | 17,037,508 |
94 | Azerbaijan | Russia and Eurasia | 43.4 | 85.2 | 36.7 | 59.5 | 43.3 | 53.7 | 0.3592 | 33,800 | 9,416,598 |
95 | Tajikistan | Russia and Eurasia | 39.9 | 78.0 | 51.1 | 57.1 | 38.5 | 51.4 | 0.3592 | 29,500 | 8,207,834 |
96 | Laos | Asia Pacific | 61.1 | 97.3 | 61.5 | 49.8 | 50.0 | 62.6 | 0.3592 | 24,300 | 6,769,727 |
97 | Kyrgyzstan | Russia and Eurasia | 68.2 | 64.3 | 45.3 | 57.0 | 43.1 | 54.2 | 0.3592 | 20,500 | 5,719,500 |
98 | Turkmenistan | Russia and Eurasia | 64.6 | 100.0 | 45.0 | 64.7 | 46.3 | 64.8 | 0.3592 | 18,800 | 5,240,072 |
99 | Timor-Leste | Asia Pacific | 71.7 | 23.0 | 60.5 | 58.2 | 57.0 | 54.2 | 0.3404 | 4,000 | 1,178,252 |
100 | Tunisia | Middle East and North Africa | 64.6 | 45.0 | 40.8 | 48.3 | 53.9 | 52.0 | 0.3063 | 33,300 | 10,886,500 |
101 | Saudi Arabia | Middle East and North Africa | 82.3 | 91.8 | 36.0 | 49.5 | 72.2 | 65.9 | 0.2919 | 84,200 | 28,828,870 |
102 | Indonesia | Asia Pacific | 47.0 | 70.0 | 51.9 | 49.6 | 56.0 | 53.7 | 0.2858 | 714,100 | 249,865,631 |
103 | Philippines | Asia Pacific | 36.4 | 41.4 | 45.6 | 52.5 | 59.4 | 47.1 | 0.2655 | 261,200 | 98,393,574 |
104 | Mauritius | Sub-Saharan Africa | 68.2 | 30.8 | 38.9 | 21.4 | 42.3 | 39.0 | 0.2541 | 3,300 | 1,296,303 |
105 | Turkey | Europe | 50.5 | 63.7 | 39.6 | 44.2 | 62.9 | 50.9 | 0.2476 | 185,500 | 74,932,641 |
106 | Ukraine | Russia and Eurasia | 57.6 | 46.0 | 38.9 | 61.1 | 40.0 | 48.0 | 0.2476 | 112,600 | 45,489,600 |
107 | Kosovo | Europe | 22.2 | 45.0 | 36.3 | 48.4 | 56.3 | 40.9 | 0.2476 | 4,500 | 1,824,000 |
108 | Gabon | Sub-Saharan Africa | 50.5 | 45.6 | 49.8 | 46.4 | 63.8 | 50.5 | 0.2476 | 4,100 | 1,671,711 |
109 | China | Asia Pacific | 57.6 | 91.9 | 42.2 | 46.2 | 53.3 | 59.0 | 0.2388 | 3,241,400 | 1,357,380,000 |
110 | Papua New Guinea | Asia Pacific | 89.4 | 28.5 | 65.9 | 48.2 | 89.3 | 65.0 | 0.2300 | 16,800 | 7,321,262 |
111 | Mexico | Americas | 39.9 | 40.9 | 39.0 | 60.2 | 42.7 | 45.2 | 0.2182 | 266,900 | 122,332,399 |
112 | Colombia | Americas | 43.4 | 43.3 | 38.7 | 57.9 | 49.2 | 45.8 | 0.2182 | 105,400 | 48,321,405 |
113 | Peru | Americas | 43.4 | 46.2 | 35.6 | 48.9 | 53.1 | 45.4 | 0.2182 | 66,300 | 30,375,603 |
114 | Ecuador | Americas | 39.9 | 49.6 | 32.2 | 57.7 | 34.7 | 42.1 | 0.2182 | 34,300 | 15,737,878 |
115 | Guatemala | Americas | 32.8 | 44.6 | 44.1 | 66.8 | 58.8 | 51.7 | 0.2182 | 33,800 | 15,468,203 |
116 | Bolivia | Americas | 54.0 | 42.3 | 53.4 | 60.5 | 48.3 | 49.5 | 0.2182 | 23,300 | 10,671,200 |
117 | Honduras | Americas | 54.0 | 53.8 | 58.0 | 75.6 | 64.4 | 61.1 | 0.2182 | 17,700 | 8,097,688 |
118 | Paraguay | Americas | 43.4 | 36.5 | 43.3 | 61.5 | 53.9 | 46.3 | 0.2182 | 14,800 | 6,802,295 |
119 | El Salvador | Americas | 32.8 | 32.6 | 44.9 | 61.4 | 53.5 | 42.9 | 0.2182 | 13,800 | 6,340,454 |
120 | Nicaragua | Americas | 8.1 | 59.6 | 60.9 | 59.7 | 41.2 | 45.9 | 0.2182 | 13,300 | 6,080,478 |
121 | Chile | Americas | 36.4 | 20.0 | 31.7 | 23.6 | 45.7 | 31.5 | 0.2095 | 36,900 | 17,619,708 |
122 | Costa Rica | Americas | 54.0 | 22.5 | 34.6 | 39.1 | 24.5 | 34.2 | 0.2095 | 10,200 | 4,872,166 |
123 | Panama | Americas | 68.2 | 28.0 | 35.6 | 46.8 | 42.6 | 42.1 | 0.2095 | 8,100 | 3,864,170 |
124 | Uruguay | Americas | 57.6 | 14.6 | 31.3 | 33.6 | 26.8 | 31.4 | 0.2095 | 7,100 | 3,407,062 |
125 | Venezuela | Americas | 43.4 | 76.4 | 38.3 | 73.7 | 35.0 | 52.7 | 0.2002 | 60,900 | 30,405,207 |
126 | South Africa | Sub-Saharan Africa | 43.4 | 24.8 | 38.2 | 46.9 | 55.6 | 43.3 | 0.2001 | 106,000 | 52,981,991 |
127 | Japan | Asia Pacific | 61.1 | 17.6 | 23.4 | 11.4 | 40.0 | 29.9 | 0.1865 | 237,500 | 127,338,621 |
128 | South Korea | Asia Pacific | 22.2 | 39.2 | 30.8 | 30.5 | 36.0 | 30.3 | 0.1865 | 93,700 | 50,219,669 |
129 | Argentina | Americas | 25.8 | 30.7 | 30.3 | 46.5 | 21.3 | 29.5 | 0.1865 | 77,300 | 41,446,246 |
130 | Poland | Europe | 1.0 | 21.7 | 27.1 | 22.2 | 48.2 | 25.5 | 0.1865 | 71,900 | 38,530,725 |
131 | Hong Kong | Asia Pacific | 64.6 | 3.5 | 21.1 | 10.9 | 25.2 | 25.0 | 0.1865 | 13,400 | 7,187,500 |
132 | Dominican Republic | Americas | 47.0 | 54.3 | 41.2 | 60.5 | 59.3 | 51.7 | 0.1754 | 18,200 | 10,403,761 |
133 | Trinidad and Tobago | Americas | 64.6 | 27.7 | 36.2 | 41.5 | 36.8 | 42.8 | 0.1690 | 2,300 | 1,341,151 |
134 | Jamaica | Americas | 36.4 | 23.9 | 54.9 | 54.5 | 49.7 | 41.7 | 0.1548 | 4,200 | 2,715,000 |
135 | Barbados | Americas | 57.6 | 17.5 | 42.3 | 23.1 | 42.3 | 38.5 | 0.1488 | 400 | 284,644 |
136 | Kenya | Sub-Saharan Africa | 78.8 | 68.5 | 54.4 | 67.3 | 56.0 | 63.6 | 0.1464 | 64,900 | 44,353,691 |
137 | Madagascar | Sub-Saharan Africa | 64.6 | 64.8 | 79.8 | 59.0 | 58.0 | 67.4 | 0.1326 | 30,400 | 22,924,851 |
138 | Belarus | Russia and Eurasia | 64.6 | 97.3 | 36.4 | 54.5 | 34.7 | 56.8 | 0.1215 | 11,500 | 9,466,000 |
139 | Romania | Europe | 25.8 | 50.1 | 34.8 | 42.8 | 40.6 | 38.1 | 0.1132 | 22,600 | 19,963,581 |
140 | Latvia | Europe | 43.4 | 34.8 | 30.0 | 38.8 | 45.1 | 37.7 | 0.1132 | 2,300 | 2,013,385 |
141 | Singapore | Asia Pacific | 22.2 | 51.9 | 28.2 | 16.8 | 59.4 | 35.1 | 0.0998 | 5,400 | 5,399,200 |
142 | Israel | Middle East and North Africa | 29.3 | 43.9 | 28.7 | 32.0 | 58.4 | 37.8 | 0.0806 | 6,500 | 8,059,400 |
143 | Brazil | Americas | 22.2 | 28.0 | 33.3 | 50.2 | 42.5 | 34.6 | 0.0775 | 155,300 | 200,361,925 |
144 | Cuba | Americas | 68.2 | 97.3 | 51.6 | 44.8 | 1.0 | 55.5 | 0.0362 | 4,100 | 11,265,629 |
145 | United States | Americas | 8.1 | 17.9 | 22.2 | 26.1 | 25.4 | 19.9 | 0.0190 | 60,100 | 316,128,839 |
146 | Italy | Europe | 32.8 | 21.9 | 24.0 | 38.1 | 31.3 | 29.6 | 0.0190 | 11,400 | 59,831,093 |
147 | Germany | Europe | 11.6 | 24.7 | 25.1 | 14.4 | 12.2 | 17.6 | 0.0130 | 10,500 | 80,621,788 |
148 | France | Europe | 25.8 | 25.8 | 28.0 | 21.0 | 23.9 | 22.8 | 0.0130 | 8,600 | 66,028,467 |
149 | United Kingdom | Europe | 8.1 | 10.3 | 17.1 | 18.4 | 17.6 | 15.1 | 0.0130 | 8,300 | 64,097,085 |
150 | Spain | Europe | 15.1 | 27.9 | 22.8 | 22.6 | 17.6 | 22.7 | 0.0130 | 6,100 | 46,647,421 |
151 | Canada | Americas | 8.1 | 16.8 | 25.4 | 11.2 | 19.7 | 15.5 | 0.0130 | 4,600 | 35,158,304 |
152 | Taiwan | Asia Pacific | 11.6 | 28.4 | 17.1 | 27.7 | 28.9 | 22.7 | 0.0130 | 3,000 | 23,340,000 |
153 | Australia | Asia Pacific | 11.6 | 2.9 | 24.8 | 13.5 | 15.1 | 11.5 | 0.0130 | 3,000 | 23,130,900 |
154 | Netherlands | Europe | 11.6 | 9.2 | 25.1 | 13.5 | 8.4 | 11.4 | 0.0130 | 2,200 | 16,804,224 |
155 | Belgium | Europe | 4.5 | 18.1 | 26.8 | 14.9 | 15.9 | 16.0 | 0.0130 | 1,500 | 11,195,138 |
156 | Greece | Europe | 36.4 | 49.8 | 30.2 | 43.3 | 50.9 | 41.4 | 0.0130 | 1,400 | 11,032,328 |
157 | Portugal | Europe | 18.7 | 13.0 | 28.2 | 17.0 | 29.7 | 21.4 | 0.0130 | 1,400 | 10,459,806 |
158 | Sweden | Europe | 8.1 | 15.7 | 26.5 | 10.1 | 10.9 | 13.5 | 0.0130 | 1,200 | 9,592,552 |
159 | Austria | Europe | 4.5 | 17.3 | 23.9 | 14.4 | 14.4 | 14.9 | 0.0130 | 1,100 | 8,473,786 |
160 | Switzerland | Europe | 32.8 | 23.3 | 21.1 | 10.6 | 25.5 | 22.0 | 0.0130 | 1,100 | 8,081,482 |
161 | Denmark | Europe | 43.4 | 16.8 | 25.2 | 3.5 | 6.2 | 18.4 | 0.0130 | 700 | 5,613,706 |
162 | Finland | Europe | 4.5 | 22.2 | 26.2 | 8.9 | 14.4 | 16.0 | 0.0130 | 700 | 5,439,407 |
163 | Norway | Europe | 11.6 | 16.0 | 25.6 | 7.8 | 2.5 | 11.3 | 0.0130 | 700 | 5,084,190 |
164 | New Zealand | Asia Pacific | 15.1 | 8.6 | 26.6 | 6.6 | 6.8 | 12.7 | 0.0130 | 600 | 4,470,800 |
165 | Luxembourg | Europe | 32.8 | 2.4 | 10.9 | 9.9 | 21.6 | 17.0 | 0.0130 | <100 | 543,202 |
166 | Ireland | Europe | 18.7 | 18.1 | 27.1 | 16.7 | 19.5 | 20.7 | 0.0070 | 300 | 4,595,281 |
167 | Iceland | Europe | 54.0 | 19.0 | 22.4 | 12.1 | 3.0 | 20.0 | 0.0070 | <100 | 323,002 |
Global Slavery Index 2013[edit]
The following is a ranking of the top 30 countries/territories in order of the lowest prevalence of modern slavery. The full rankings can be found in the Walk Free Foundation's website.[12]
1. Iceland, Ireland, United Kingdom
4. New Zealand
5. Austria, Belgium, Denmark, Finland, Greece, Luxembourg, Norway, Sweden, Switzerland
14. Cuba
15. Portugal, Spain
17. Costa Rica
18. Panama
19. Canada
20. Mauritius
22. Singapore
23. Hong Kong
24. France, Netherlands
25. Australia
26. South Korea
27. Germany
28. Barbados
29. United States
30. Trinidad and Tobago
31. Italy
32. Latvia
33. Japan
References[edit]
- ^ "Global Slavery Index". Walk Free Foundation. Retrieved 26 August 2015.
- ^ "Global Slavery Index Methodology" (PDF). Walk Free Foundation. Retrieved 26 August 2015.
- ^ "Government Response". globalslaveryindex.silk.co.
- ^ "Using Surveys to Estimate Prevalence of Modern Slavery" (PDF).
- ^ a b Datta, Monti Narayan; Bales, Kevin (November 2013). "Slavery in Europe: Part 1, Estimating the Dark Figure". Human Rights Quarterly 35 (4): 818–829. doi:10.1353/hrq.2013.0051. Retrieved 15 April 2015.
- ^ Jacqueline Joudo Larsen, Monti Narayan Datta and Kevin Bales, "Modern Slavery", Significance, Volume 12, Issue 5, pages 22–43, October 2015
- ^ Walk Free Foundation. "Methodology" (PDF). The Global Slavery Index. Walk Free Foundation. Retrieved 15 April 2015.
- ^ Andrew Guth, Robyn Anderson, Kasey Kinnard and Hang Tran, Proper Methodology and Methods of Collecting and Analyzing Slavery Data: An Examination of the Global Slavery Index, in Social Inclusion (open access journal), Vol. 2, No 4 (2014), pp. 14-22, article posted on the Cogitatio website on 17 November 2014: "The Global Slavery Index aims to, among other objectives, recognize the forms, size, and scope of slavery worldwide as well as the strengths and weaknesses of individual countries. An analysis of the Index’s methods exposes significant and critical weaknesses and raises questions into its replicability and validity" (summary of the article) - "The formation and implementation of sound policy is not possible without sound data. The methodology and methods used in the Index are currently inadequate and therefore the Index cannot be validated or replicated. Furthermore, the publicity given to the Index is leading to the use of this poor data not only by popular culture and reputable magazines and news organizations [...], but also by academic journals and high level policy makers [...], which can lead to inaccurate policy formulation and a compounding of harm [...]" (p. 19).
- ^ "Economist Online: Performance indices - International comparisons are popular, influential—and sometimes flawed". http://www.economist.com. Retrieved 2014-11-16.
- ^ "GSI 2014 Global Data and codebook". The Global Slavery Index. Walk Free Foundation. Retrieved 12 January 2015.
- ^ Direct download of XLS table: GSI 2014 Global Data and codebook
- ^ "Walk Free Foundation – Global Slavery Index 2013 | Home - Walk Free Foundation - Global Slavery Index 2013". globalslaveryindex.org. Retrieved 2014-06-05.
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