Party manifestos from 23 European countries are analyzed for their salience of the gig economy. The dataset contains 188 election manifestos from parliamentary elections between 2018 and 2022. Johanna Plenter created this replication data for a study examining which parties address the issue and the influencing factors.
Use Cases
- Train a classifier to predict party family (e.g., left-wing) from manifesto text features related to gig economy keywords.
- Analyze the frequency and context of gig economy keyword mentions across different countries and election years.
- Build a multilevel model to estimate the effect of country-level factors on the probability of a manifesto addressing the gig economy.
- Conduct a comparative analysis of manifesto text to identify framing differences in discussions of self-employment and labor practices.
Strengths
- Contains 188 party manifestos for analysis.
- Covers 23 European countries, enabling cross-national comparison.
- Data is temporally focused on a recent period (2018-2022).
Limitations
- Gig economy is discussed in only about 30% of the manifestos, indicating a sparse target variable.
- Sample size of 188 documents may limit the statistical power for some subgroup analyses.
- The analysis is confined to Europe, limiting generalizability to other regions.
Provenance
- Source
- Harvard Dataverse, authored by Johanna Plenter.
- Collection Method
- Data gathered via keyword-in-context analysis of party election manifestos.
- Time Range
- 2018 to 2022
- Freshness
- Data covers elections up to 2022, with a repository update in 2026.
- Geography
- 23 European countries