Research with moirée

The moirée database opens up various research perspectives. The following questions are intended as starting points — not as an exhaustive list:

1. Prevalence of experience types by industry: Which forms of structural disadvantage dominate in which sectors? Are there industry-specific patterns (e.g., Gatekeeping in Audio, Tokenism in Games)?
2. Regional patterns in the DACH region and beyond: Do the documented experiences differ between Germany, Austria, and Switzerland? What changes emerge with the EU expansion of the platform?
3. Career level and vulnerability: Are those early in their careers more affected than those in senior positions? Do experience types differ by career level?
4. Temporal trends: Are certain experience types increasing or decreasing over time? Are there seasonal or economic patterns?
5. Overlap of multiple experience types: Do affected individuals report overlapping patterns? Do certain combinations occur more frequently (e.g., Invisible Labor and Tokenism)?

An overview of existing academic literature can be found on the Studies page. Please also note the known limitations of the database.

moirée provides anonymized case studies with structured metadata for scientific use. Each case contains information on experience type, industry, region, state, career level, time period, and short and full-text descriptions. The data is linked to academic studies and categorized according to scientific standards.

Data formats:

• CSV export — available via the database page (filtering and download)
• JSON file — structured case data in data/cases-export.json (Open Source, MIT License)

All data and content are available under Creative Commons CC BY 4.0 — free to use with attribution.

In the docs/data-package/ directory you will find:

• Codebook — Variable documentation for all data fields
• Methodology Summary — Summary of the data collection methodology
• Limitations — Known limitations and notes
• Citation Guide — Citation formats (BibTeX, APA, Chicago)

moirée is open to scientific collaborations. Possible forms of cooperation:

• Joint publications — Co-authorship on analyses and evaluations of the data
• Data analysis partnerships — Access to raw data for your own research projects
• Methodology review — Assessment and further development of the data collection methodology

What the platform offers:

• Open data access under CC BY 4.0
• Methodological guidance and documentation
• Opportunity for co-authorship on data-driven publications

If you are interested in a collaboration, please use the form below:

There are currently no active research projects in cooperation. If you are interested in a collaboration, please contact us via the form above.