BBC Radio 4 · Broadcast Bias Monitor · 2026

The news isn't
biased by accident.

Fred Bias monitors BBC Radio 4's flagship news programmes every day. Automated analysis. Evidence-based scoring. Published openly. No agenda except the evidence.

Get Early Access How It Works
4 BBC programmes
monitored daily
7 Analytical
dimensions
42 Bias techniques
detected
Rolling 30-day scores · BBC Radio 4 Updated daily
Today Programme
Mon–Sat · 06:00–09:00
Highly Biased
71
World at One
Mon–Fri · 13:00–13:45
Moderately Biased
58
PM
Mon–Fri · 17:00–18:00
Moderately Biased
62
The World Tonight
Mon–Fri · 22:00–22:45
Mildly Biased
43
Scores are illustrative pre-launch · Live data coming soon About the score →
Today Programme · 71 Highly Biased Language asymmetry detected in Gaza coverage · 34 episodes World at One · 58 Moderately Biased Passive voice used for Palestinian deaths in 67% of reports PM · 62 Moderately Biased Think tank guests: 34 appearances without funding disclosure The World Tonight · 43 Mildly Biased Yemen coverage: 4% of Ukraine coverage time in same period Today Programme · 71 Highly Biased Language asymmetry detected in Gaza coverage · 34 episodes World at One · 58 Moderately Biased Passive voice used for Palestinian deaths in 67% of reports PM · 62 Moderately Biased Think tank guests: 34 appearances without funding disclosure The World Tonight · 43 Mildly Biased Yemen coverage: 4% of Ukraine coverage time in same period

What Fred Bias Does

Systematic. Automated.
Evidence-based.

Fred Bias monitors BBC Radio 4's flagship news programmes every day. Every episode is automatically transcribed, segmented into individual interviews, reports, and features, and analysed across seven dimensions of bias.

The result is a daily bias score — the Bias-Meter — published openly, with every finding backed by specific transcript evidence that anyone can read and challenge.

No human coder. No editorial agenda. No exceptions. The same analytical standard applied to every episode, every programme, every day.

01 · EPISODE ANALYSIS
Every episode scored daily
Each broadcast is transcribed, segmented, and scored within hours of airing. Individual bias reports for every episode, every day.
02 · SEGMENT EXTRACTION
Interview-by-interview breakdown
Fred identifies every interview, news report, and feature within an episode. [08:14] Nick Robinson interviews Rishi Sunak on NHS waiting times (4m 32s).
03 · TREND ANALYSIS
Patterns over months and years
Monthly scorecards. Trend lines. Is the bias worsening? Which topics show the most consistent asymmetry? The data tells the story.
04 · INTELLIGENT SEARCH
Ask Fred anything about BBC coverage
"Show me every interview about Gaza in the last six months." Natural language queries over the entire transcript database.

The Bias-Meter

A score you can cite. Evidence you can check.

The Bias-Meter is a 0–100 score calculated across seven analytical dimensions. Every score cites specific transcript evidence. Every methodology step is published. Every finding can be challenged.

90–100
Severely
Biased
70–89
Highly
Biased
50–69
Moderately
Biased
30–49
Mildly
Biased
10–29
Mostly
Fair
0–9
Fair

What the score is. And what it isn't.

The Bias-Meter score is not a judgment of individual journalists or of the BBC as an institution. It is a measurement of structural patterns in a specific episode across seven measurable dimensions.

A score of 65 does not mean the Today programme lied. It means that across seven dimensions, this episode showed consistent patterns that align with documented forms of bias. The score is reproducible, auditable, and challengeable.

The BBC is invited to respond to any finding. Fred will publish every substantiated response.

METHODOLOGY
Published in full at fredbias.com/methodology. Every dimension, every technique, every weighting. Fully transparent and challengeable.
EVIDENCE
Every finding cites the specific transcript passage that triggered it. No verdict without evidence. No exception.
RIGHT OF REPLY
The BBC is formally invited to respond to every published score. Substantiated responses are published alongside the original finding.

Seven Analytical Dimensions

What Fred measures — and how.

Every episode is scored across seven dimensions. Each dimension produces a sub-score. The weighted average is the Bias-Meter score.

D1
Language & Framing
20% weight
Loaded language, passive voice to erase agency, euphemism, scare quotes, emotional language asymmetry — tracked per 1,000 words with actor attribution.
D2
Source Balance
20% weight
Guest affiliation audit, challenge asymmetry per guest type, first and last voice analysis, think tank disclosure tracking.
D3
Topic Prominence
15% weight
Time allocation by story, region, and population. Systematic under-representation of non-Western populations flagged and scored.
D4
Narrative Ordering
10% weight
Whose perspective leads each report. Whose comes last. Consistency of ordering across the episode — who is always primary.
D5
Omission Detection
15% weight
Cross-referenced against Reuters, AP, and Al Jazeera wire. Stories prominent elsewhere but absent from BBC flagged and assessed.
D6
Emotional Language
10% weight
"Horrific", "tragic", "devastating", "barbaric" — which events trigger strong language and which do not. Asymmetry by actor and conflict.
D7
False Balance & Framing
10% weight
False equivalence, protagonist/antagonist framing, manufactured consensus, both-sidesing structural inequality between powerful and powerless.

Why Fred Bias Is Different

No other system does all of this.

Media Lens is manual. Cardiff University is academic and slow. NewsGuard rates outlets, not programmes. Ofcom only responds to complaints. Fred does something none of them do.

✓ Continuous
Every episode, every day
No gaps. No cherry-picking. The full output of four programmes monitored automatically without human curation.
✓ Segment-level
Interview by interview
Not just episode scores — every individual interview, report, and feature analysed separately. Challenge asymmetry per presenter.
✓ Presenter-level
Individual journalist profiles
Every presenter accumulates a bias profile over time. Does Nick Robinson challenge government ministers as hard as opposition politicians?
✓ Searchable
Natural language queries
"How does Today describe Hamas vs Israeli forces?" Types a question. Gets an answer with cited evidence from the transcript database.
✓ Public-facing
Open to everyone
Core scores and reports are free and public. Bias monitoring that only paying subscribers can see is bias monitoring that can be dismissed.
✓ Evidence-based
Every verdict cites its source
No score without specific transcript evidence. No technique applied without showing exactly which passage triggered it. Fully auditable.

Who It's For

Built for everyone who cares about accurate information.

✍️
Primary audience
Journalists & Freelancers
Contextualise BBC sources within documented bias patterns. Know the programme's track record before you cite it. Check whether a claim came from a programme scoring 71 on Gaza coverage.
🏛️
Institutional
Newsrooms & Editorial Teams
Editorial quality benchmarking. Legal protection through documented due diligence. API integration with your CMS. Monthly bias briefings in Fred's house style.
🎓
Academic
Researchers & Academics
Years of transcript data, structured and queryable. The kind of longitudinal analysis Cardiff and Glasgow Media Group produce manually — available as a dataset.
📣
Civil society
Campaigners & NGOs
Independent, evidence-based data to support advocacy. Citable scores from a published methodology. Not opinion — measurement.
⚖️
Regulatory
Ofcom & Parliamentary Bodies
Systematic, continuous monitoring data available for regulatory proceedings, parliamentary inquiries, and BBC governance reviews.
🌍
Public
Anyone Who Watches the News
You pay for the BBC. You have a right to know how it's performing. The core Bias-Meter scores are free, public, and plain English.

Coming Soon · 2026

The information system
is not neutral.

Fred Bias launches later this year. Be the first to know when live monitoring begins — and get early access to the full database.

Message Fred on WhatsApp hello@fredcheck.com

Also available via fredcheck.com · Same account · Same standard