8 datasets found
  1. Indicator 16.2.2: Detected victims of human trafficking for forced labour...

    • data-isdh.opendata.arcgis.com
    • sdgs.amerigeoss.org
    • +2more
    Updated Sep 9, 2021
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    UN DESA Statistics Division (2021). Indicator 16.2.2: Detected victims of human trafficking for forced labour servitude and slavery by age and sex (number) [Dataset]. https://data-isdh.opendata.arcgis.com/datasets/undesa::indicator-16-2-2-detected-victims-of-human-trafficking-for-forced-labour-servitude-and-slavery-by-age-and-sex-number
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    Dataset updated
    Sep 9, 2021
    Dataset provided by
    United Nations Department of Economic and Social Affairshttps://www.un.org/en/desa
    Authors
    UN DESA Statistics Division
    Area covered
    Description

    Series Name: Detected victims of human trafficking for forced labour servitude and slavery by age and sex (number)Series Code: VC_HTF_DETVFLRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 16.2.2: Number of victims of human trafficking per 100,000 population, by sex, age and form of exploitationTarget 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of childrenGoal 16: Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levelsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

  2. Indicator 16.2.2: Detected victims of human trafficking for sexual...

    • sdg.org
    • sdgs.amerigeoss.org
    • +1more
    Updated Sep 23, 2021
    + more versions
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    UN DESA Statistics Division (2021). Indicator 16.2.2: Detected victims of human trafficking for sexual exploitaton by age and sex (number) [Dataset]. https://www.sdg.org/datasets/indicator-16-2-2-detected-victims-of-human-trafficking-for-sexual-exploitaton-by-age-and-sex-number/api
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    Dataset updated
    Sep 23, 2021
    Dataset provided by
    United Nations Department of Economic and Social Affairshttps://www.un.org/en/desa
    Authors
    UN DESA Statistics Division
    Area covered
    Description

    Series Name: Detected victims of human trafficking for sexual exploitaton by age and sex (number)Series Code: VC_HTF_DETVSXRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 16.2.2: Number of victims of human trafficking per 100,000 population, by sex, age and form of exploitationTarget 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of childrenGoal 16: Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levelsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

  3. h

    Data from: Screening for Human Trafficking among Refugees in Germany [Data...

    • heidata.uni-heidelberg.de
    pdf, png, tsv
    Updated Dec 19, 2023
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    Estella Tambini Stollwerck; Ivo Rollmann; Hans-Christoph Friederich; Christoph Nikendei; Estella Tambini Stollwerck; Ivo Rollmann; Hans-Christoph Friederich; Christoph Nikendei (2023). Screening for Human Trafficking among Refugees in Germany [Data and Analysis] [Dataset]. http://doi.org/10.11588/DATA/DUNN8C
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    tsv(22814), png(319272), tsv(3376), tsv(5412), tsv(3566), pdf(1239210), tsv(4274)Available download formats
    Dataset updated
    Dec 19, 2023
    Dataset provided by
    heiDATA
    Authors
    Estella Tambini Stollwerck; Ivo Rollmann; Hans-Christoph Friederich; Christoph Nikendei; Estella Tambini Stollwerck; Ivo Rollmann; Hans-Christoph Friederich; Christoph Nikendei
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Mali, Islamic Republic of, Iran, Mauritania, India, Russian Federation, Tunisia, Afghanistan, Nigeria, Iraq, Yemen
    Dataset funded by
    Ministry of Justice Baden-Württemberg
    Description

    Background: Human trafficking occurs all over the world and its true extent is still unknown. What we know is that the actual number of trafficked persons is significantly higher than the number of registered cases in Europe or anywhere else. Human trafficking is particularly likely among refugees, as they easily fall for false promises due to language barriers, lack of knowledge on the local culture and difficult living conditions. Therefore, the purpose of this study was to create a screening tool to identify survivors of human trafficking among refugees in a German state registration and reception centre. Method: In a joint project with the Ministry of Justice of Baden-Württemberg and the Regional Administrative Authority of Karlsruhe (“Regierungspräsidium”), we asked new arrivals at the initial reception centre in Heidelberg on a weekly basis from December 2021 to June 2022 about their experiences with human trafficking. We used a combination of the eight questions of the Adult Human Trafficking Screening Tool and one screening question borrowed from a publication by Mumma et al. to address all forms of exploitation. If trafficking indeed was the case, was validated by face-to-face contacts with forced migrants screened positive. Results: Overall, 13 of the 176 asylum seekers had experienced trafficking, which corresponded to a prevalence of 7.3%. The dichotomous questionnaire had a sensitivity of 76.9% and a specificity of 84.0% at a newly selected cut-off of six positive responses. In an exploratory descriptive analysis on subregions, refugees from West Africa had a substantially higher prevalence (33.3%) for trafficking in human beings within our sample and in this subgroup, mainly female refugees were affected by trafficking. In comparison, there were hardly any gender differences in the represented parts of the rest of the world in our study. Conclusion: The modified form of the AHTST distinguishes reliably those who had experienced human trafficking from other refugees. The high prevalence of trafficking in most regions, regardless of gender, suggests that more effort is needed to identify and protect trafficked persons.

  4. Modern Slavery ⛓

    • kaggle.com
    zip
    Updated Jan 20, 2025
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    Patrick L Ford (2025). Modern Slavery ⛓ [Dataset]. https://www.kaggle.com/patricklford/modern-slavery
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    zip(6478 bytes)Available download formats
    Dataset updated
    Jan 20, 2025
    Authors
    Patrick L Ford
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Introduction

    "Slavery was an ugly, dirty business but people of virtually every race, colour, and creed engaged in it on every inhabited continent. And the people they enslaved were also of virtually every race, colour, and creed." ~ Thomas Sowell

    The persistence of slavery throughout human history, spanning all continents and involving people of diverse backgrounds, underscores its deeply ingrained and universal nature. Despite its historical prevalence, modern slavery manifesting as forced labour, human trafficking, forced marriage and the exploitation of children (mainly girls), continues to plague millions worldwide. This project aims to explore the contemporary dimensions of slavery, highlighting its root causes, human impact, and the urgent need for collective action to eradicate it from our world. By understanding the complex legacy of slavery, we can better address its modern iterations and work toward a future of freedom and dignity for all.

    Recommended Reading

    We did not weave the web of life ! We are merely a strand in the web. link

    A previous project of mine on Kaggle. Where I concentrate on some important factors that will affect humanity's potential to survive on planet Earth: - Global Demographic Shifts. - Inequality. - Climate change. - Resource depletion.

    The Global Slavery Index 2023

    The Global Slavery Index 2023 by the Walk Free Foundation offers an updated analysis of modern slavery worldwide, covering forms such as forced labour, forced marriage, debt bondage, human trafficking, and child exploitation. link WalkFree

    Key Insights:

    • Global Increase: In 2021, approximately 50 million people were living in modern slavery, a 25% increase over the last five years.
    • Regional Distribution: The Asia-Pacific region accounts for the largest share, with 29.3 million people in modern slavery.
    • Highest Prevalence Rates: Countries with the highest rates of modern slavery per 1,000 population include:
      • North Korea: 104.6 per 1,000 people.
      • Eritrea: 90.3 per 1,000 people.
      • Mauritania: 32.0 per 1,000 people.
    • G20 Nations: These nations collectively account for more than half of all modern slavery cases. Among them, India leads with an estimated 11 million people in forced labour.

    Contributing Factors:

    • Climate Change: Environmental degradation increases susceptibility to exploitation.
    • Armed Conflict: Conflict zones experience heightened rates of modern slavery.
    • Weak Governance: Inadequate legal frameworks and enforcement exacerbate the issue.
    • Health Emergencies: Crises like the COVID-19 pandemic have amplified vulnerabilities.

    Recommendations for Action:

    • Legislation: Strengthen laws to prevent the use of goods and services linked to modern slavery.
    • Sustainability Integration: Embed anti-slavery measures in climate and sustainability policies.
    • Educational Initiatives: Provide educational opportunities to reduce vulnerability.
    • Regulatory Oversight: Enforce stricter regulations on child marriage and supply chain transparency.

    Modern Slavery at a Glance

    The Global Estimates of Modern Slavery 2021, produced by the International Labour Organisation (ILO), Walk Free, and the International Organisation for Migration (IOM), are the foundation for the national statistics presented in Walk Free’s Global Slavery Index 2023. link ILO

    This report provides insights into:

    • Prevalence & Numbers: Estimates of modern slavery across 160 countries, derived from household surveys and vulnerability assessments.
    • Vulnerability: Analyses factors that make communities more susceptible to modern slavery based on 23 indicators across five dimensions.
    • Government Response: Assesses efforts in 176 countries based on 141 indicators across five milestones, highlighting policies, programs, and progress.

    The report also highlights goods imported by G20 countries that are at risk of being linked to forced labour, encouraging transparency and accountability in supply chains.

    Global Estimates of Modern Slavery. Forced Labour and Forced Marriage. link ILO pdf

    Data Visualisation; Global_Slavery_Index_2023.csv

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2Fab97194d984ae475378c2b0e791cb864%2FScreenshot%202025-01-20%2012.26.14.png?generation=1737381194059542&alt=media" alt="">

    ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2Fb2ebd0e70b03...

  5. D

    HIDTA/ HIFCA (High Intensity Drug Trafficking Area/ High Intensity Financial...

    • dataandsons.com
    csv, zip
    Updated Sep 8, 2021
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    Zigram Data Technologies Pvt Ltd (2021). HIDTA/ HIFCA (High Intensity Drug Trafficking Area/ High Intensity Financial Crimes Area) [Dataset]. https://www.dataandsons.com/categories/business-information-and-financials/hidta-hifca-high-intensity-drug-trafficking-area-high-intensity-financial-crimes-area
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    csv, zipAvailable download formats
    Dataset updated
    Sep 8, 2021
    Dataset provided by
    Data & Sons
    Authors
    Zigram Data Technologies Pvt Ltd
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    About this Dataset

    A Comprehensive list of areas falling under HIDTA and HIFCA list in the United States. HIDTA/ HIFCA is the world’s most comprehensive and largest data asset based on High Intensity Drug Trafficking Areas and High Intensity Financial Crimes Areas located in the US. There are currently 33 HIDTAs, and HIDTA-designated counties are in 50 states, as well as in Puerto Rico, the U.S. Virgin Islands, and the District of Columbia. And there are currently 7 HIFCA regions that cover the United States, the US Virgin Islands, and Puerto Rico. As of August 2021, this data asset consolidates Data with all Counties along with State, Cities, Town and Zip codes/Area Codes. The notable point of this database is the inclusion of the risk rating score for all customers within high-risk geographies by a number of arbitrarily defined “points”. Thus, they could more easily exceed a defined risk rating point threshold and be deemed “high-risk. Users can access this data by directly contacting ZIGRAM via sending an email to siddharth.sabu@zigram.tech. Pricing available on request.

    Category

    Business Information & Financials

    Keywords

    HIDTA,HIFCA,Drug Trafficking,Financial Crimes

    Row Count

    50

    Price

    $250.00

  6. World Drug Report 2021 (UNODC)

    • kaggle.com
    zip
    Updated Aug 27, 2022
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    Craig Chilvers (2022). World Drug Report 2021 (UNODC) [Dataset]. https://www.kaggle.com/datasets/craigchilvers/world-drug-report-2021-unodc
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    zip(320662 bytes)Available download formats
    Dataset updated
    Aug 27, 2022
    Authors
    Craig Chilvers
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    The following dataset is the World Drug Report 2021 produced by the United Nations Office on Drugs and Crime. https://www.unodc.org/unodc/en/data-and-analysis/wdr2021_annex.html

    The Executive Summary: https://www.unodc.org/res/wdr2021/field/WDR21_Booklet_1.pdf

    Special points of interest from the report: - Cannabis has come to be seen as less risky by adolescents from 1995 to 2019, but the herb potency has increased 4x in that time period. - Web-based sales have increased dramatically. - Number of drug users in Africa is projected to rise by 40 per cent by 2030, based on expected population growth in the 15-64 demographic. - Drug markets quickly recovered after the onset of the pandemic, but some trafficking dynamics have been accelerated during Covid-19 - Non-medical use of cannabis and sedatives has increased globally during the pandemic

    On Opioids specifically: - The two pharmaceutical opioids most commonly used to treat people with opioid use disorders, methadone and buprenorphine, have become increasingly accessible over the past two decades. The amount available for medical use has increased sixfold since 1999, from 557 million daily doses in that year to 3,317 million by 2019. - The amounts of fentanyl and its analogues seized globally have risen rapidly in recent years, and by more than 60 per cent in 2019 compared with a year earlier. Overall, these amounts have risen more than twenty-fold since 2015. The largest quantities were seized in North America. - Elsewhere in the world, other pharmaceutical opioids (codeine and tramadol) predominate. Over the period 2015–2019, the largest quantities of tramadol seized were reported in West and Central Africa; they accounted for 86 per cent of the global total. Codeine was intercepted in large quantities in Asia, often in the form of diverted cough syrups. - Almost 50,000 people died from overdose deaths attributed to opioids in the United States in 2019, more than double the 2010 figure. By comparison, in the European Union, the figure for all drug-related overdoses (mostly relating to opioid use) stood at 8,300 in 2018, despite the larger population. - However, the opioid crisis in North America is evolving. The number of deaths attributed to heroin and the non-medical use of pharmaceutical opioids such as oxycodone or hydrocodone has been declining over the past five years. - The crisis is now driven mainly by overdose deaths attributed to synthetic opioids such as fentanyl and its analogues. Among the reasons for the large number of overdose deaths attributed to fentanyls is that the lethal doses of them are often small when compared with other opioids. Fentanyl is up to 100 times more potent than morphine. - The impact of fentanyl is illustrated even further by the fact that more than half of the deaths attributed to heroin also involve fentanyls. Synthetic opioids also contribute significantly to the increased number of overdose deaths attributed to cocaine and other psychostimulants, such as methamphetamine.

  7. Data from: A dataset of the crackdown on cross-border wildlife crimes in...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Mar 28, 2023
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    Tianjian Song; Zexu Luo; Yuxin Huang; Yonghua Li; Lei Fang; Jiang Chang (2023). A dataset of the crackdown on cross-border wildlife crimes in China, 2014-2020 [Dataset]. http://doi.org/10.5061/dryad.t1g1jwt5g
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    zipAvailable download formats
    Dataset updated
    Mar 28, 2023
    Dataset provided by
    Chinese Research Academy of Environmental Sciences
    University of Chinese Academy of Sciences
    Authors
    Tianjian Song; Zexu Luo; Yuxin Huang; Yonghua Li; Lei Fang; Jiang Chang
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    China
    Description

    Wildlife crimes that involve smuggling threaten national security and biodiversity, cause regional conflicts, and hinder economic development, especially in developing countries with abundant wildlife resources. Over the past few decades, significant headway has been made in combating wildlife smuggling and the related illegal domestic trade in China. Previous studies on the wildlife smuggling trade were mostly based on customs punishment and confiscation data. From the China Judgments Online website, we retrieved cases related to cross-border wildlife and wildlife products smuggling from 2014 to 2020. A total of 510 available cases and 927 records for more than 110 species were registered. We thoroughly studied each judgment and ruling file to extract information on cases, defendants, species, sentences, and origins and destinations of wildlife and wildlife products. Furthermore, frequency of origin-destination place occurrences and spatial patterns of cross-border wildlife crime in China were shown in this data paper. The main purpose of our dataset is to make these wildlife and wildlife products trade data accessible for researchers to develop conservation studies. We expect that this dataset will be valuable for network analysis of regional or global wildlife trafficking, which has attracted global attention. There are no copyright restrictions on the data; we ask that researchers please cite this paper and the associated dataset when using the data in publications. Methods Data source: The China Judgments Online (CJO) website (https://wenshu.court.gov.cn) provides electronic public access to court records. In 2010, 2013, and 2016, the Supreme People’s Court promulgated and revised the provisions on the publication of judicial documents by people’s courts on the Internet, and the publication of judicial documents has become the responsibility and obligation of courts at all levels (Wu, 2022). Since January 1, 2014, judgment documents must be published on CJO within seven days of their enforcement, and cannot be amended, replaced or revoked without court authority. Up to now, the CJO has become an important channel for the publication of judgments documents.

    Data collection: The collection time of this dataset is up to September 2021. We searched for “wildlife” and “smuggling” on the China referee’s website. Then, we screened these judgment documents according to the following criteria: (I) the full text can be accessed, and the case involves the crimes of illegal hunting, sale, acquisition, transportation, or smuggling of wildlife or wildlife products (including rare and endangered wildlife or wildlife products) overseas and (II) when there are multiple judgment documents in the same lawsuit, such as any subsequent retrial of a case, filing and hearing of different perpetrators in batches, a consistent case number (record) was assigned.

    Data compilation: These judicial documents provide the process of tracing criminal information. We collected as detailed information as possible, such as the date of the seizure, the location of the seizure, the type of illegal activities, the items seized, the source of the items seized, and the actual or expected destination. We used these criteria: (I) on the premise of protecting the personal information in the judgment documents, we obtained the education level and nationality of the principal defendants; (II) for the origin and destination of wildlife or its products, in addition to recording the national, provincial, county, and city levels, the information should be as accurate as possible to specific geographical names by obtaining longitude and latitude coordinate data through Baidu map (https://map.baidu.com/) and Google map (https://www.google.com/maps); and (III) for the identification of “crocodile,” “modern elephant,” “pangolin scale,” and other identifications that are not accurate to the species level in the judgment documents, only the upper classification (genus) level was recorded (i.e., “Crocodylus,” “Loxodonta,” “Manis”; Figure 3). If only the Chinese common name of the species was given but the Latin scientific name was not given, we queried the corresponding species in the International Union for the Conservation of Nature (IUCN)’s Red List of Threatened Species (hereafter: IUCN Red List; https://www.iucnredlist.org) for supplemental information. Eventually these records were translated from Chinese to English.

    Quality control: Due to the need to extract information by reading many parties’ statements, defenders’ opinions, examination instructions, and other words, the preliminary preparation was mainly to discuss the standardized methods and steps of data collection, and the division of labor and training of personnel involved in data collection tasks. In the data entry and summary stage, established data collection methods and steps were followed to reduce human errors. In the data inspection stage, we cross checked the obtained data and missing values with the author to ensure the accuracy of data input. If there were questions, the lead author and Luo would revisit the original judgment documents and make a final decision after discussion with the other authors.

  8. Indicator 8.7.1: Proportion of children engaged in economic activity by sex...

    • sdgs.amerigeoss.org
    • sdg-template-cat-sdgs.opendata.arcgis.com
    • +2more
    Updated Sep 23, 2021
    + more versions
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    UN DESA Statistics Division (2021). Indicator 8.7.1: Proportion of children engaged in economic activity by sex and age (percent) [Dataset]. https://sdgs.amerigeoss.org/datasets/undesa::indicator-8-7-1-proportion-of-children-engaged-in-economic-activity-by-sex-and-age-percent
    Explore at:
    Dataset updated
    Sep 23, 2021
    Dataset provided by
    United Nations Department of Economic and Social Affairshttps://www.un.org/en/desa
    Authors
    UN DESA Statistics Division
    Area covered
    Description

    Series Name: Proportion of children engaged in economic activity by sex and age (percent)Series Code: SL_TLF_CHLDEARelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 8.7.1: Proportion and number of children aged 5–17 years engaged in child labour, by sex and ageTarget 8.7: Take immediate and effective measures to eradicate forced labour, end modern slavery and human trafficking and secure the prohibition and elimination of the worst forms of child labour, including recruitment and use of child soldiers, and by 2025 end child labour in all its formsGoal 8: Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for allFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

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UN DESA Statistics Division (2021). Indicator 16.2.2: Detected victims of human trafficking for forced labour servitude and slavery by age and sex (number) [Dataset]. https://data-isdh.opendata.arcgis.com/datasets/undesa::indicator-16-2-2-detected-victims-of-human-trafficking-for-forced-labour-servitude-and-slavery-by-age-and-sex-number
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Indicator 16.2.2: Detected victims of human trafficking for forced labour servitude and slavery by age and sex (number)

Explore at:
Dataset updated
Sep 9, 2021
Dataset provided by
United Nations Department of Economic and Social Affairshttps://www.un.org/en/desa
Authors
UN DESA Statistics Division
Area covered
Description

Series Name: Detected victims of human trafficking for forced labour servitude and slavery by age and sex (number)Series Code: VC_HTF_DETVFLRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 16.2.2: Number of victims of human trafficking per 100,000 population, by sex, age and form of exploitationTarget 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of childrenGoal 16: Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levelsFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

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