This is the Dataverse with the published datasets of the HUB Global Labour Conflicts project. This dataverse is maintained by the International Institute of Social History (IISG) (https://iisg.amsterdam/en) on behalf of the network. Any questions or suggestions can be addressed to ...

The datasets are grouped into so-called "Dataverses" of different levels. To see those levels, click on the tick box "Dataverses" on the left panel.

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You will see 5 dataverses:
  • Remarkable Strikes: These are qualitative accounts of a few selected, exceptional historical strikes.
  • Global Labour Conflicts: Contains the aggregated dataset on labour conflicts for more than 250 countries.
  • Micro Labour Conflicts: Datasets with more detailed accounts of specific (periods of) labour disputes.
  • Aggregate data: Datasets with aggregated data per country for certain time periods.
  • National Labour Conflicts: Datasets with aggregated data per country for certain time periods.

    For researchers with a focus on The Netherlands, the main dataset of interest is "Labour Conflicts in the Netherlands, 1372-2019" (https://hdl.handle.net/10622/APNT4U). This dataset has been converted to linked open data. The converted version can be queried using a sparql endpoint here: https://druid.datalegend.net/IISG/Labourconflicts. For users who are not able to query sparql directly, we provide a "Data story" with a simpler way to enter query terms. There are two data stories for the Dutch dataset:
  • A data story where you can get an overview of the data model: data story: data-model
  • A data story where you can get insights into the data itself, with the most common queries (per year, occupation, place, etc.): data story: dataset queries

    More information about the HUB Global Labour Conflicts and these data can be found here: https://iisg.amsterdam/en/blog/hub-global-labour-conflicts, and in this publication: Aurich, J., Simpson, C., & Kösters, R. (2022). Workers’ resistance across time and space. Arbetarhistoria, 183(3). https://doi.org/10.52024/tseg.14505.

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    Advanced Search

    91 to 100 of 229 Results
    Canada, 1960-2015
    Feb 2, 2018 - Aggregate data
    Linda Briskin, 2018, "Canada, 1960-2015", https://hdl.handle.net/10622/M0Z1TS, IISH Data Collection, V1
    Tables collected by Linda Briskin from the Workplace Information and Research Division (WIRD) for the period 1960-2015.
    National_Canada_1960-2015_explanatory text.doc
    Feb 2, 2018 - Canada, 1960-2015
    MS Word - 43.5 KB - MD5: 3d7f3dbcfae8c9970ba5f0f20c3ccdae
    National_Canada_1960-2015..xlsx
    Feb 2, 2018 - Canada, 1960-2015
    MS Excel Spreadsheet - 60.5 KB - MD5: 6b6451513d5eb1bb467cce16a73f28b0
    B_World_1800-2017.tab
    Jan 9, 2018 - Global
    Tabular Data - 571 B - 7 Variables, 31 Observations - UNF:6:3jH+9Jqtv3Y6LOU2c5VPHQ==
    Global file updated with most recent ILO decent (December 2017)
    Canada, 1960-1967
    Nov 13, 2017 - Micro Labour Conflicts
    Rosero Abad, Sofia, 2017, "Canada, 1960-1967", https://hdl.handle.net/10622/V0F8S1, IISH Data Collection, V1, UNF:6:iIdk/Yd8yzEDMmvxIO2O0Q== [fileUNF]
    Micro data from official publications.
    Micro_Canada_1960-1967.tab
    Nov 13, 2017 - Canada, 1960-1967
    Tabular Data - 29.7 KB - 15 Variables, 188 Observations - UNF:6:iIdk/Yd8yzEDMmvxIO2O0Q==
    Micro Canada_explanatory text_Dept. of Labour_1960-1967.doc
    Nov 13, 2017 - Canada, 1960-1967
    MS Word - 29.5 KB - MD5: 2ec49c1fcef77a0d9a07bf5bfe85b837
    Argentina, 1907-1930
    Oct 27, 2017 - National Labour Conflicts
    van der Velden, Sjaak, 2017, "Argentina, 1907-1930", https://hdl.handle.net/10622/HZPAQS, IISH Data Collection, V1, UNF:6:DZKtyARYwwSuFTDTayd7cQ== [fileUNF]
    Number of strikes taken from official sources by Ronaldo Munck and examined by Lucas Poy
    National_Argentina, 1907-1930.tab
    Oct 27, 2017 - Argentina, 1907-1930
    Tabular Data - 563 B - 25 Variables, 3 Observations - UNF:6:DZKtyARYwwSuFTDTayd7cQ==
    National_Argentina_explanatory text_1907-1930.doc
    Oct 27, 2017 - Argentina, 1907-1930
    MS Word - 29.5 KB - MD5: ec9336537f603095dbeacdd39b0697e1
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