SVFAB

What we measure has never existed in any country in the world before.


SVFAB analyses public broadcasting systematically, AI-assisted and primary-source-based — for balance, omission bias and compliance with the legal mandate. Not as opinion. As measurement.

No research institute worldwide has ever analysed public broadcasting with this level of systematisation, methodology and scope for legal balance. This is a key finding from exchanges with media scientists worldwide.

SVFAB is the first and only organisation in the world to have built this.

 

The Swiss Association for Balanced Reporting (SVFAB) is a non-profit organisation committed to fairness and plurality of opinion in the Swiss media.
David Schläpfer – President, with expertise in IT, psychology, law and socio-political engagement.
Jürg Rückmar – Active contributor in organisation and public outreach.

We work with members, supporters and volunteers from all walks of life who share our vision of a balanced, fact-based public discourse.

 

We are doing what the SRG itself recommended.

In 2016, SRG SSR commissioned the Gottlieb Duttweiler Institute (GDI) to produce a foundational study on its future. The GDI defined “integration performance” as the most important quality criterion for a public broadcaster — and explicitly recommended verifying it with measurable criteria.

That recommendation went unfollowed. SVFAB is implementing it: independently, systematically, AI-assisted — with over 25,000 analysed broadcasts dating back to 1968.

Measurement, not opinion.

>200k
CHF Self-Investment
Since 2021

5+
Years of Systematic Development
Methodology, corpus, infrastructure

25,000+
Broadcasts Analysed
SRG/SRF, ARD/ZDF, NRK

4
Countries in Corpus
CH, DE, NL, NO

4
Languages
DE, FR, IT, EN

7.03/10
Omission Bias Ø
What’s missing is missing structurally

10+
Publications
Books, reports, methodology

16
International Scientists
13 countries, active 2026

10
Years of Time Series
Structurally analysed

“No research institute worldwide has so far built a comparable system for the systematic AI-assisted analysis of public service broadcasts.”

7.03 / 10
Omission Bias Ø
What is missing, is missing structurally

3 Countries
CH · DE · NO
Corpus growing continuously

‘No research institute in the world has ever built a comparable system for the systematic AI-assisted analysis of public broadcasting.’