Revised README, translations
Ein harter, ehrlicher Blick in den Spiegel ist die Grundlage für eine nachhaltige, zukunftsorientierte Gesellschaft. Heute, da entschieden wird, wer an der Spitze der politischen Pyramide in der Schweiz steht, möchten wir die Arbeit von Forscher/innen und Journalist/innen, Unternehmen und Non-Profit-Organisationen hervorheben, die sich für die Gleichstellung und für Gender Data einsetzen.
Un regard dur et honnête dans le miroir est le fondement d'une société durable et tournée vers l'avenir. Aujourd'hui, alors que l'on décide qui se trouve au sommet de la pyramide politique en Suisse, nous souhaitons mettre en lumière le travail des chercheurs et des journalistes, des entreprises et des organisations à but non lucratif qui s'efforcent de combler l'écart entre les données sur les hommes et les femmes.
Guardarsi allo specchio con onestà è il fondamento di una società sostenibile e orientata al futuro. Oggi, mentre si decide chi siederà al vertice della piramide politica in Svizzera, vorremmo sottolineare il lavoro di ricercatori e giornalisti, aziende e organizzazioni no-profit che lavorano per colmare il divario tra i dati di genere.
A hard & honest look in the mirror is the foundation of a sustainable, future-oriented society. Today, as it is decided who stands at the top of the political pyramid in Switzerland, we would like to highlight the work of researchers and journalists, businesses and non-profits working to close the gender data gap.
If you Mind the gap:
- 🧗 Share knowledge at forum.opendata.ch
- 👓 Collect more open data in this github repo
- 📔 Read Invisible Women: Exposing Data Bias in a World Designed for Men by Caroline Criado Perez
The photo in the header (CC BY 4.0 Oleg Lavrovsky) is of a poster at the Effinger Kaffeebar & Coworking Space, crowdsourcing stories of inspiring feminist leadership.
This is a Data Package made with the Open Data Application, started as part of the Open Data Advent Calendar 2023.
We are collecting sample datasets and links on gender inequality and gender (mis)representation here. You are welcome to suggest others in the Issues, or upload your own files into the [data/] folder, update this README with another section, and start a Pull Request.
Lohnanalyse.ch
This is a crowdsourced dataset representing the difference in salaries between common jobs in Switzerland. Neithe we nor its authors make any claims of accuracy or representativeness. There is currently no indication on the data source website that the data is protected by copyright, or may be redistributed under a certain license - and we will update this notice when we get their response.
Copy and paste the data from Lohnanalyse.ch, apply some regular expressions to clean it up, and paste it into a spreadsheet. There does not seem to be a way at the moment to export the data, and no automated process to scrape the data exists at the moment.
Please get permission from Lohnanalyse.ch for using this data for any purposes non-commercial, commercial, or otherwise.
Here is an example visualization of the top 10 male and top 10 female discrepancies:
Download the chart in English or German here.
License
This Data Package - which includes the metadata, but not necessarily any data redistributed along with it - is made available by its maintainers @loleg and @viktoria-molnar under the ODC Open Database License (ODbL), a copy of the full text of which is in LICENSE.md.
In the spirit of community and love to your fellow humankind.
♀️♂️⚧️
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