Global Slavery Index

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The Global Slavery Index is an annual ranking of slavery conditions by countries world wide (2013 n = 162, 2014 n = 167) published by the Walk Free Foundation.[1] In 2013, the first Global Slavery Index included information about the prevalence, vulnerability and country-level national responses. In 2013 the Index itself is calculated based on a combined measure of three factors:

In 2014, the methodology was substantially updated.[2] The 2014 Global Slavery Index includes three data points for each country: national estimates of the prevalence of modern slavery, vulnerability measures and an assessment of the strength of government responses.[3] The Index pioneered the use of random-sampled, nationally-representative surveys to estimate prevalence. This included commissioning seven 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.

Calculation[edit]

The 2014 Global Slavery Index includes data on three key variables: the prevalence of modern slavery in each country, vulnerability, and 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 the estimates in the 2014 Global Slavery Index involved several steps:

  • Clustering: countries were grouped into seven clusters, based on their degree of similarity for factors relevant to vulnerability of enslavement. 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.
  • Extrapolation: survey data on the prevalence of slavery (expressed as a percentage of the population) that was available for each cluster was then used to estimate the prevalence 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 and 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 comparative test of 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. All but one of the extrapolated estimates of the prevalence of slavery fell within one percentage point of the estimates derived from random sample surveys.[6]

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]

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. They claim that 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]

Some countries, for which no data were available, were given the same rate as countries that 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 form of extrapolation has attracted some criticism.[9]

Global Slavery Index 2014[edit]

Global Slavery Index 2014 table[10][11]
  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]

  1. ^ "Global Slavery Index". Walk Free Foundation. Retrieved 26 August 2015. 
  2. ^ "Global Slavery Index Methodology" (PDF). Walk Free Foundation. Retrieved 26 August 2015. 
  3. ^ "Government Response". globalslaveryindex.silk.co. 
  4. ^ "Using Surveys to Estimate Prevalence of Modern Slavery" (PDF). 
  5. ^ 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. 
  6. ^ Jacqueline Joudo Larsen, Monti Narayan Datta and Kevin Bales, "Modern Slavery", Significance, Volume 12, Issue 5, pages 22–43, October 2015
  7. ^ Walk Free Foundation. "Methodology" (PDF). The Global Slavery Index. Walk Free Foundation. Retrieved 15 April 2015. 
  8. ^ 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).
  9. ^ "Economist Online: Performance indices - International comparisons are popular, influential—and sometimes flawed". http://www.economist.com. Retrieved 2014-11-16.  External link in |publisher= (help)
  10. ^ "GSI 2014 Global Data and codebook". The Global Slavery Index. Walk Free Foundation. Retrieved 12 January 2015. 
  11. ^ Direct download of XLS table: GSI 2014 Global Data and codebook
  12. ^ "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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