This piece examines the impact of AI on New Zealand's workforce, highlighting job displacement across sectors, the potential need for universal basic income and reskilling, and the broader societal risks and opportunities arising from AI adoption.
How the framings classify across 5 articles. Each framing is labelled by a small AI stance classifier; see the methodology page for details.
Up to 12 framings across outlets and orientations — each a short phrase the extractor generated to characterise the piece's editorial angle (not a quote). Filter by lean to see how each bloc is spinning the story; click through to read the original.
a future threat requiring adaptive social safety nets
The Country 14/07/26: Daniel Eb talks to Jamie MackayLobby groups, unions, think tanks and industry bodies whose own releases or whose people’s media appearances touched this topic over the last 12 months. Owned = their own press releases; earned = their people quoted across radio, press & commentary. A card carried in both — with the release coming first — is the agenda-setting signal. Co-occurrence isn’t proof a group drove the coverage.
risk of social disruption through mass redundancy
Stacked weekly counts; colour by lean. “n/a” covers government and iwi-Māori sources where lean isn't applicable.
How this topic has been named, week by week. A new alias winning out is usually a framing shift.
How the news corpus has covered this same topic over the last 12 weeks. 4 articles from RNZ, Stuff, NZ Herald, ODT, 1News, Newsroom and The Spinoff. Click through to the press view for the full panel.
Verbatim segments from politicians speaking on podcasts and radio shows about this topic. Sourced via the voice-reference library — each speaker has been confirmed manually from their voice clip. Click play to stream the original audio from the publisher, pre-seeked to the moment the quote starts.
Well, this is a really interesting story, isn't it? The latest RNZ poll out suggesting that if the opportunity party was to get far past five percent and they're currently …
Social-media signal on the same topic, drawn from the social lens. Engagement is likes + 2×shares + 3×replies, the same weighting used across the digest cards. View on /social →
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