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3 results for “German Occupation”
France under German occupation. The German and French administration 1940-1945 – full data
<p>At <a href="http://www.adresses-france-occupee.fr">www.adresses-france-occupee.fr</a>, the GHIP provides an interactive map showing the German and French authorities in France during the German occupation of France between 1940 and 1945. In addition to the historical and current address, the website provides information about the tasks, responsibilities and the structure of each department of the authorities, as well as photos if available. Depending on the type and scope of the query, it gives an impression of everyday life, the presence of the German occupation administration and forces and, last but not least, their cooperation with the French authorities. The information is based on a systematic evaluation of the telephone books of the German authorities and French administration directories from the time of the war. They were completed by research in German and French archives, in particular the <em>Archives municipales</em>, as well as press media, historical map collections and research works.</p> <p>With this entry we give access to the data of this database in four different tables (csv UTF-8 and excel).</p> <p>1) The table "services" relates to the departments (German: <em>Dienststellen</em>). The data is maintained in the state closest to that of the phone directories and address books: a department is valid in a hierarchy at a given address and at a given time. The table contains:</p> <p>· the ID number (id), its linking to its superior department (parent_service_id)</p> <p>· the name of the department (name),</p> <p>· the ID number of the source from which the information originates (source_id),</p> <p>· the ID number of the place where the departments office is located (place_id),</p> <p>· the status on the website (status: visible, pending, deleted),</p> <p>· the display of the hierarchy (d_breadcrumb) and</p> <p>· the last edit of the entry by the project team (last_edit_date).</p> <p>There are 68,044 entries in total.</p> <p> </p> <p>2) The table "service_bridge" is a cross table, relating the departments to each other by showing their hierarchy. IT contains the parent_service_id, the child_service_id, and the breadcrumb, that indicates the department's position in the hierarchy. There are 28,162 entries in total</p> <p> </p> <p>3) The table "places" is used to localise the departments. A place is a geographical point identified by its latitude and longitude. The address (in text format) of this place may have changed over time. The database contains both old and new names. The table contains the ID number of the place (id), the name of the building/accommodation (name), the status of the entry on the website (status: visible, pending, deleted), the current address (current_country, current_zip, current_city, current_street, current_house_number), former address (fromer_street, former_house_number) as well as the longitude and latitude of the place. There are 15,454 entries in total.</p> <p> </p> <p>4) The table "sources_details" relates to the sources used to build the database. By source we understand ‘data source’, i.e. any source used to obtain information on the German and French authorities of the time. We mostly used German and French telephone directories of the years 1940–1944. The table contains:</p> <p>· the ID number of the source (id),</p> <p>· the name of the source in short (name),</p> <p>· the country of publication or origin of the source (country),</p> <p>· the full edition date (edition_date) if available, otherwise approximate,</p> <p>· the year of the publication or year of the source (d_edition_year),</p> <p>· the month of the publication or month of the source (d_edition_month) and</p> <p>· the full bibliographical citation and/or explanations (source_name_complete).</p> <p>There are 57 entries in total.</p> <p>You can get in touch with us via the mail dh [at] dhi-paris.fr</p>
Supplementary material for a mixed-methods study on research impact in a study on lived experiences of German occupation children
<p>Study material (questionnaire) as well as material regarding the qualitative analysis of open-ended questions, s.a. category system, analysis table, additional statistic analyses.</p> <p> </p> <p>Supplement 1: Questionnaire used in the study</p> <p>Supplement 2: Category system of qualitative analysis with sample quotes</p> <p>Supplement 3: Analysis table of qualitative analysis with all corresponding quotes</p> <p>Supplement 4: Statistical comparison of responders (participating in the impact study) to non-responders of the initial study on lived experiences</p>
German Twitter Data on Occupations
<h1>Background</h1> <p>There are many valuable insights on jobs and professions in different sectors of society based on their imminent and ascribed characteristics. Studying such characteristics traditionally was done by action research, surveys, questionnaires, etc. which typically take much time and resources to be concluded. This dataset accompanies our studies where we examine vocational education and training data on Twitter. We presented a generic framework to retrieve, process and analyze tweets, and discussed research questions from computational social science: For example, how can we make Twitter data interoperable to other<br>available resources, e.g. classifications of occupations, tools and skills? Second, do we have enough data to process job collocational prestige analysis on a geographical basis? This presents a novel approach towards labor market research, making novel data interoperable which has not been considered in previous literature. Our approach and pipeline is generic and could be easily extended to other languages. It also contributes to prestige research by widening the question of ascribed prestige to the question of how information on occupations is collocated and what these contextualization tell us about how occupations are seen.</p> <h1>Data</h1> <p>This dataset contains the metadata related to 3,407,481 tweets (2007-2023). However, according to Twitter/X rules of data protection, we do not publish any data retrieved by their API. This dataset contains a unique id (not the tweet id), a job_id related to KldB (Klassifikation der Berufe), a job_title linked to that tweet, a timestamp and a sentiment. </p> <h1>Contact</h1> <p>Please contact us if you have questions or want to use this dataset.</p>
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