European Institute for Gender Equality (EIGE)
EIGE
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European Institute for Gender Equality, Gedimino pr. 16, LT-01103 Vilnius, Lithuania
+370 5 215 7444
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November 2022
The data is based on a survey implemented in 10 selected EU countries: Denmark, Finland, France, Latvia, the Netherlands, Poland, Romania, Slovakia, Slovenia, and Spain. The data was collected from November and December 2020, and had 4,932 respondents, aged 16-54.
The survey respondents were individuals who reported to be platform workers among daily internet users. These are workers who use online platforms (e.g. Uber, Wolt, Bolt) to access clients and deliver specific tasks or services.
The main objective of EIGE’s survey was to increase the understanding of gender differences in the working conditions, work patterns and work-life balance of women and men engaged in platform work. Both the survey design and the data collection time frame ensured coverage of the impact of the COVID-19 pandemic.
The survey data was collected via a web survey using the existing international panel platform CINT.
Further information (including a technical report) about the survey can be found here.
The indicators are grouped into eight themes, reflecting key areas covered within the survey:
The following classification systems are relevant for the Platform Workers indicators:
The basis of response options for level of education was the ISCED 2011 classification of eight education levels (UNESCO Institute for Statistics, 2012).
The basis of the classification of on-location services and web-based remote services was the JRC typology of digital labour markets, which distinguishes between micro-tasking, tasking, physical services and interactive services.
Types of income are classified according to the EU-SILC 2018 classification of personal income components, excluding near cash income (e.g., company car) and including a category for ‘Income from work via online platforms’. Several categories were combined for brevity (pension from individual private plans, state pension (old-age benefits), survivor’s benefits (e.g., widows, widowers, orphans); sickness and disability benefits).
The response categories regarding income status correspond to those used in Eurostat’s (2020a) Survey on the Usage of ICT in Household and by Individuals (ICT usage survey), although the question and its answer options are formulated by combining several questions from the survey. Also comparable to LFS data.
The concept "platform work" refers to workers who use online platforms (e.g. Uber, Wolt, Bolt) to find and conclude contracts to deliver specific tasks or services.
For a list of national and international labour platforms, see the survey technical report (available here).
The statistical unit is the individual.
The target population for this survey was platform workers, among daily internet users, in ten selected Member States, aged between 16 and 54 years.
Denmark, Spain, France, Latvia, the Netherlands, Poland, Romania, Slovenia, Slovakia and Finland.
2020
2020
Most indicators are expressed as percentages of all relevant respondents. In some cases the unit used was average number of hours of work or care.
2020
The European Institute for Gender Equality (EIGE) has been given a mandate to monitor progress on achieving the objectives of the Beijing Platform for Action (BPfA) in the EU. This data relates to Area F, ‘Women and the economy’.
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No direct identification of a person is possible from the indicators based on the survey.
Data processing, validation and coding have been carried out in accordance with the requirements listed under Regulation (EU) 2018/1725. In order to guarantee respondent anonymity, personal identification variables were excluded from microdata delivered to EIGE.
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EIGE publishes the results in its dedicated Gender Statistics Database.
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No regular news releases.
Results from the Platform Workers Survey are published by EIGE in the report ‘Beijing Platform for Action: Artificial Intelligence, platform work and gender equality’ (2021).
No micro-data are disseminated.
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Available upon request
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Steps taken during the collection of data to support data quality include:
No quality concerns have been identified.
This data is relevant to decision-makers and others in relation to on-going policy and legal changes related to platform work, for example, the proposed directive on the working conditions of people working through digital labour platforms.
No user opinions have been collected.
The sample size is considered reliable for all 10 Member States selected for the survey.
The data are considered to be of high accuracy.
None identified.
Non-sampling errors related to individual responses. 451 respondents (platform workers) were removed from the dataset after quality and validity checks.
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The same methodology was applied across countries, and as such the data can be considered comparable. The use of population size weights also supports cross-country comparison of results.
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Each Platform worker survey indicator included in the Gender Statistics Database has full internal coherence, as it is based on the same data source.
Not revision planned.
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EIGE’s survey of Platform Workers, conducted in 2020.
The platform workers survey was a one-off activity.
Multivariate validation procedures identified interrelated variables and used logical checks to find errors or inconsistencies. A specific weight, ranging from 0.5 to 1, for each of the tests implemented in data cleaning was assigned. All respondents achieving a weighted flag score of 3 or more were removed from the sample. In total, 451 respondents (platform workers) were removed from the dataset after quality and validity checks.
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Weighting was applied following comparison of the sample (including both platform workers and those disqualified from the survey) with the official statistics on daily internet users provided by Eurostat (2020c). This showed that people with low formal education were underrepresented in all countries. Men aged between 25 to 54 years were also underrepresented when compared with the overall population.
To reduce these discrepancies, post-stratification weighting was carried out. To avoid bias, the survey was weighted using a calibration procedure.
Three weights were computed using the same procedure: