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  • Digital Humanities and Cultural Her...
  • North American Studies

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Luck, Patrick;

    The Louisiana Runaway Slave Advertisements Database (LRSAD) contains information about 861 individuals who appeared in 691 advertisements placed in Louisiana (predominantly New Orleans) newspapers between 1801 and 1820. These advertisements were mostly placed by enslavers wishing to capture someone who they claimed to enslave but had escaped or by sheriffs and jailers alerting the public that a person who was African or of African descent had been jailed on suspicion of being a runaway slave. These advertisements are somewhat unique in North America in that they often include information on individuals’ places of origin and language skills. American Antiquarian Society, Worcester, Massachusetts; Library of Congress' Early State Records Project, Law Library Microform Consortium; Louisiana Newspaper Project, Louisiana Digital Library; Louisiana State Museum, New Orleans, Louisiana; New Orleans Public Library, New Orleans, Louisiana; Tulane University, New Orleans, Louisiana

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Harvard Dataversearrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Harvard Dataverse
    Dataset . 2023
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Harvard Dataversearrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Harvard Dataverse
      Dataset . 2023
      Data sources: Datacite
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Onuch, Olga; Arkwright, Cressida; Bodini, Astrid; Doyle, David; +9 Authors

    The MOBILISE project examines why some people respond to discontent by protesting, others by migrating while yet others stay immobile. It focuses on four countries that have seen outmigration and protest in recent year (Ukraine, Poland, Morocco and Argentina) and migrants from these countries who live in Germany, the United Kingdom and Spain. The main body of MOBILISE survey data are nationally representative face-to-face surveys in Ukraine, Poland, Morocco and Argentina. As these surveys are unable to capture (current) migrants from these countries – a group that is crucial to answering the MOBILISE research question – MOBILISE employs a migrant survey targeted at three destination countries; Germany, the UK and Spain. MOBILISE migrant surveys were closely oriented to the national surveys in order to achieve the longitudinal nature of the data. All of the surveys thoroughly ask for political views and beliefs as well as socio economic background, the reasons and motivations to (or not) migrate and the reason to (or not) protest. The migrant survey was run online. We also ran two supplementary online national surveys targeting the general population in Ukraine and Argentina. All MOBILISE national and migrant surveys are set-up as a two wave panel. The first wave of data collection for the migrant and national survey started in September 2019 and finished in March 2020. The second wave started between December 2020 and December 2021. This data deposit contains wave one and two of the migrant and national online surveys (the nationally representative surveys are deposited separately).

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao CESSDA Data Catalogu...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    UK Data Archive
    Dataset . 2023
    Data sources: Datacite
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao CESSDA Data Catalogu...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      UK Data Archive
      Dataset . 2023
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Newman, Simon P;

    Newspaper advertisements written and published by enslavers seeking the capture and return of enslaved people who had escaped. Published in the Kingston Daily Advertiser, Jamaica, January-December 1791. This dataset is a part of the Magazine of American Datasets (MEAD). To view more of the collection, visit https://repository.upenn.edu/exhibits/orgunit/mead.

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    https://doi.org/10.48659/hsrg-...
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      https://doi.org/10.48659/hsrg-...
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Olin, Per;

    System log files are filled with logged events, status codes, and other messages. By analyzing the log files, the systems current state can be determined, and find out if something during its execution went wrong. Log file analysis has been studied for some time now, where recent studies have shown state-of-the-art performance using machine learning techniques. In this thesis, document classification solutions were tested on log files in order to classify regular system runs versus abnormal system runs. To solve this task, supervised and unsupervised learning methods were combined. Doc2Vec was used to extract document features, and Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) based architectures on the classification task. With the use of the machine learning models and preprocessing techniques the tested models yielded an f1-score and accuracy above 95% when classifying log files.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Digitala Vetenskapli...arrow_drop_down
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Digitala Vetenskapli...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ali, Ayesha;

    The history of California is in many ways a story about water, and the outsized effect that droughts, floods, and seasonal precipitation rates have had on the political and economic development of the state over the past 170 years. This thesis uses discourse analysis of historical and ongoing negotiations that have been presented in federal and state reports, narratives, case laws and legislation to explore how the discourse around water politics has been shaped in the state. From this, an antiessentialist environmental history develops around the relationship between overdrafted groundwater basins in the Central Valley and the agriculture industry located there. Finally, this thesis explores what the future of a waterscape built during the capitalization of modern society may look like as we move towards a new regime of nature.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Publikationer från U...arrow_drop_down
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Publikationer från U...arrow_drop_down
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    Authors: Taylor, Jordan E.;

    Newspapers and newspaper printers played a crucial role in brokering the sales of enslaved people in eighteenth-century North America. This dataset collects information from more than 2,100 newspaper advertisements that document printers’ involvement in trafficking thousands of enslaved people. It extends from 1704, when the first long-running newspaper was published in North America, through 1807, after which the transatlantic slave trade officially ended and gradual abolition schemes in the north meant that the internal slave trade shifted slowly to the South. The dataset is useful for those interested in newspaper printers’ involvement in the internal slave trade, as well as particular transactions involving enslaved people. It includes available information about the subjects of each advertisement, as well as the terms of sale or transfer proposed by the advertiser. The newspapers utilized here were accessed via Readex's America's Historical Newspapers database and Newspapers.com. Note that while many of these newspapers continued publication past 1807, this dataset only includes advertisements through that year. Some newspapers were consulted for this project that are not included in the list above, or in the dataset, because they did not return any relevant results. Most of those are newspapers published for only a short time.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Harvard Dataversearrow_drop_down
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    Harvard Dataverse
    Dataset . 2021
    Data sources: Datacite
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      Harvard Dataverse
      Dataset . 2021
      Data sources: Datacite
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    Dataset contains supplementary data for the article "Drivers of Holocene palsa distribution in North America" by Fewster et al. Specifically, Dataset S1 contains the catalogue of modern palsas and peat plateaus in North America used to fit our binary logistic regression model; Dataset S2 contains modern climate data extracted from the CRU TS 4.02 climatology for each grid cell in our study area and also presents the presence/absence of peat, the timing of deglaciation, peat initiation, and terrestrial drainage; Dataset S3 contains the palaeoclimate data extracted from equilibrium-type HadCM3 simulations and used to simulate past distributions of the climate envelope; Dataset S4 contains the peatland basal date catalogue used to constrain timings of peat initation in North America; and Dataset S5 contains the Spearman's Rank correlation matrix for each variable included in our final model.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Mendeley Dataarrow_drop_down
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    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Mendeley Data
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    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Mendeley Data
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data
    Dataset . 2020
    License: CC BY
    Data sources: Datacite
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    DANS-EASY
    Dataset . 2020
    Data sources: B2FIND
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      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Mendeley Data
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      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Mendeley Data
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      Mendeley Data
      Dataset . 2020
      License: CC BY
      Data sources: Datacite
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      DANS-EASY
      Dataset . 2020
      Data sources: B2FIND
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    Authors: Bon-Harper, Sara; Stetz, Nancy;

    <b>Enslaved Lives Documented in the Slaveholding of James Monroe, Virginia Planter and Political Figure,</b> 1774-1836 is a dataset of 178 individuals who are known from the documentary record to have been enslaved by James Monroe during his adulthood. The primary contribution of the work is to identify and document individual lives from inconsistent sources where they appear, often with incomplete identifying information. The dataset encompasses Monroe’s households in the city of Fredericksburg, Virginia, in Albemarle, King George, Loudoun, and Westmoreland Counties, Virginia, Washington, DC, and New York City.

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    Harvard Dataverse
    Dataset . 2022
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    Authors: Little, Paige; Madarang, Allen; Senh, Samory;

    In the 1930s, students at Prairie View State Normal & Industrial College, under the direction of the college’s registrar and Arts and Sciences director, John Brother Cade, participated in a project to interview 229 formerly enslaved individuals from 17 states in the United States, as well as Indian Territory and Canada. Nearly early 70 years since the 1863 Emancipation Proclamation, many of these individuals experienced the tail end of slavery as an institution in America, and this project aimed to capture their voices, experiences, and the hardships that they faced in the early years of their lives. Students sought out information regarding food, clothing, housing facilities, quality of life, epistemology, family, and treatment, to capture the perspective of formerly enslaved individuals and the institution of slavery. This dataset, whose fields were extracted from the documents in this archival collection housed at Southern University, compiles key pieces of information these ex-slaves shared with Prairie View students. Contributor: Iona Hextall, University of Glasgow

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    Harvard Dataverse
    Dataset . 2023
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      Harvard Dataverse
      Dataset . 2023
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    Authors: Evholt, David; Larsson, Oscar;

    Macroeconomic forecasting is a classic problem, today most often modeled using time series analysis. Few attempts have been made using machine learning methods, and even fewer incorporating unconventional data, such as that from social media. In this thesis, a Generative Adversarial Network (GAN) is used to predict U.S. unemployment, beating the ARIMA benchmark on all horizons. Furthermore, attempts at using Twitter data and the Natural Language Processing (NLP) model DistilBERT are performed. While these attempts do not beat the benchmark, they do show promising results with predictive power. The models are also tested at predicting the U.S. stock index S&P 500. For these models, the Twitter data does improve the accuracy and shows the potential of social media data when predicting a more erratic index with less seasonality that is more responsive to current trends in public discourse. The results also show that Twitter data can be used to predict trends in both unemployment and the S&P 500 index. This sets the stage for further research into NLP-GAN models for macroeconomic predictions using social media data. Makroekonomiska prognoser är sedan länge en svår utmaning. Idag löses de oftast med tidsserieanalys och få försök har gjorts med maskininlärning. I denna uppsats används ett generativt motstridande nätverk (GAN) för att förutspå amerikansk arbetslöshet, med resultat som slår samtliga riktmärken satta av en ARIMA. Ett försök görs också till att använda data från Twitter och den datorlingvistiska (NLP) modellen DistilBERT. Dessa modeller slår inte riktmärkena men visar lovande resultat. Modellerna testas vidare på det amerikanska börsindexet S&P 500. För dessa modeller förbättrade Twitterdata resultaten vilket visar på den potential data från sociala medier har när de appliceras på mer oregelbunda index, utan tydligt säsongsberoende och som är mer känsliga för trender i det offentliga samtalet. Resultaten visar på att Twitterdata kan användas för att hitta trender i både amerikansk arbetslöshet och S&P 500 indexet. Detta lägger grunden för fortsatt forskning inom NLP-GAN modeller för makroekonomiska prognoser baserade på data från sociala medier.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Luck, Patrick;

    The Louisiana Runaway Slave Advertisements Database (LRSAD) contains information about 861 individuals who appeared in 691 advertisements placed in Louisiana (predominantly New Orleans) newspapers between 1801 and 1820. These advertisements were mostly placed by enslavers wishing to capture someone who they claimed to enslave but had escaped or by sheriffs and jailers alerting the public that a person who was African or of African descent had been jailed on suspicion of being a runaway slave. These advertisements are somewhat unique in North America in that they often include information on individuals’ places of origin and language skills. American Antiquarian Society, Worcester, Massachusetts; Library of Congress' Early State Records Project, Law Library Microform Consortium; Louisiana Newspaper Project, Louisiana Digital Library; Louisiana State Museum, New Orleans, Louisiana; New Orleans Public Library, New Orleans, Louisiana; Tulane University, New Orleans, Louisiana

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    Harvard Dataverse
    Dataset . 2023
    Data sources: Datacite
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      Harvard Dataverse
      Dataset . 2023
      Data sources: Datacite
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Onuch, Olga; Arkwright, Cressida; Bodini, Astrid; Doyle, David; +9 Authors

    The MOBILISE project examines why some people respond to discontent by protesting, others by migrating while yet others stay immobile. It focuses on four countries that have seen outmigration and protest in recent year (Ukraine, Poland, Morocco and Argentina) and migrants from these countries who live in Germany, the United Kingdom and Spain. The main body of MOBILISE survey data are nationally representative face-to-face surveys in Ukraine, Poland, Morocco and Argentina. As these surveys are unable to capture (current) migrants from these countries – a group that is crucial to answering the MOBILISE research question – MOBILISE employs a migrant survey targeted at three destination countries; Germany, the UK and Spain. MOBILISE migrant surveys were closely oriented to the national surveys in order to achieve the longitudinal nature of the data. All of the surveys thoroughly ask for political views and beliefs as well as socio economic background, the reasons and motivations to (or not) migrate and the reason to (or not) protest. The migrant survey was run online. We also ran two supplementary online national surveys targeting the general population in Ukraine and Argentina. All MOBILISE national and migrant surveys are set-up as a two wave panel. The first wave of data collection for the migrant and national survey started in September 2019 and finished in March 2020. The second wave started between December 2020 and December 2021. This data deposit contains wave one and two of the migrant and national online surveys (the nationally representative surveys are deposited separately).

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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    UK Data Archive
    Dataset . 2023
    Data sources: Datacite
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao CESSDA Data Catalogu...arrow_drop_down
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      UK Data Archive
      Dataset . 2023
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Newman, Simon P;

    Newspaper advertisements written and published by enslavers seeking the capture and return of enslaved people who had escaped. Published in the Kingston Daily Advertiser, Jamaica, January-December 1791. This dataset is a part of the Magazine of American Datasets (MEAD). To view more of the collection, visit https://repository.upenn.edu/exhibits/orgunit/mead.

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    https://doi.org/10.48659/hsrg-...
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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      https://doi.org/10.48659/hsrg-...
      Dataset . 2022
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      Data sources: Datacite
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    Authors: Olin, Per;

    System log files are filled with logged events, status codes, and other messages. By analyzing the log files, the systems current state can be determined, and find out if something during its execution went wrong. Log file analysis has been studied for some time now, where recent studies have shown state-of-the-art performance using machine learning techniques. In this thesis, document classification solutions were tested on log files in order to classify regular system runs versus abnormal system runs. To solve this task, supervised and unsupervised learning methods were combined. Doc2Vec was used to extract document features, and Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) based architectures on the classification task. With the use of the machine learning models and preprocessing techniques the tested models yielded an f1-score and accuracy above 95% when classifying log files.

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    Authors: Ali, Ayesha;

    The history of California is in many ways a story about water, and the outsized effect that droughts, floods, and seasonal precipitation rates have had on the political and economic development of the state over the past 170 years. This thesis uses discourse analysis of historical and ongoing negotiations that have been presented in federal and state reports, narratives, case laws and legislation to explore how the discourse around water politics has been shaped in the state. From this, an antiessentialist environmental history develops around the relationship between overdrafted groundwater basins in the Central Valley and the agriculture industry located there. Finally, this thesis explores what the future of a waterscape built during the capitalization of modern society may look like as we move towards a new regime of nature.

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    Authors: Taylor, Jordan E.;