Global Slavery Index

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:

• Estimated prevalence of modern slavery by population (using primary and secondary data sources)
• A measure of child marriage
• A measure of human trafficking in and out of each country.

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

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

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

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

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

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. 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.

External links

• Official website