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What the picker changes
  • Top topics digest — the cards score the selected period against the prior 4 weeks.
  • 12-week heatmap & outlet matrix — show the 12 weeks ending at the selected week (they slide back with the picker, they aren’t a fixed snapshot).
  • Per-topic volume / alias drift — same 12-week trailing window, anchored on the selected period.
  • Coverage gap quadrant — scores the selected period against the 12 weeks before it (not including it).
  • Anomaly cards — only show alerts the detector fired during the selected period. Quiet weeks legitimately show none.
What stays as-is
  • Outlet orientation strip / lean colours — context-only, drawn from the last 12 weeks of activity regardless.
  • Co-occurrence graph — recent-activity anchored, not picker-driven.
  • Source & topic profiles — all-time data for the topic; the picker doesn’t affect them.
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Topic

Economic Resilience Planning

39 items · 20 aliases · peaked week of 24 May 2026 · first seen 28 Apr 2026

The piece critiques New Zealand’s inadequate preparedness for economic shocks, drawing on historical lessons from the 1979 oil crisis and current supply chain vulnerabilities, while calling for stronger investment in energy resilience, economic planning, and policy foresight.

Stance breakdown Methodology →

How the framings classify across 11 articles. Each framing is labelled by a small AI stance classifier; see the methodology page for details.

64%
27%
9%
Supportive 7 Critical 3 Neutral / explainer 1

Volume by source orientation Methodology →

Stacked weekly counts; colour by lean. “n/a” covers government and iwi-Māori sources where lean isn't applicable.

Alias drift

How this topic has been named, week by week. A new alias winning out is usually a framing shift.

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In the press Methodology →

How the news corpus has covered this same topic over the last 12 weeks. 6 articles from RNZ, Stuff, NZ Herald, ODT, 1News, Newsroom and The Spinoff. Click through to the press view for the full panel.

12-week press volume 6 articles
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Heard on radio

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, look, I think in the budget, you know, what we're trying to do is, you know, and I think a lot of your farmers would understand this. The books are in terrible shape, and everyone understands that they cranked up the debt. Um, you know, there's you know, cranked up spending, inflation interest rates went through the roof, all that good, you know, horrible stuff. But we're getting the books back in order. The reason we're doing that is so that we can keep taxes low. Uh the reason we're doing that is to keep debt low. Uh and actually us having you know a good set of books is actually how you manage uh yourself in a really volatile sort of place. But you know, you're seeing investments like wild and pines, you'll continue to see savings that are generated as we've been doing from the get-go from the back office of the bureaucracy and then redeployed into roads and hospitals and schools. We're very committed, obviously, to the RMA reforms that are coming through the system. Um and so, you know, really it's about continuing to fix the basics that Labour broke, and it's about building up the future into infrastructure, education, defence, trade, RMO, those sorts of things that have a real benefit for regional communities.
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Sample framings

Up to 12 framings spread across orientations. Each framing is a short phrase the topic extractor generated to characterise the piece's stance — not a quote from the source. Click through to read the original.

linked to national stability and institutional confidence

Social cohesion means different things to Clark and Luxon, both flawed
10 Jun
pundit Centre

under-invested in despite clear warnings

Responding to the Economic Shocks from the Iran War
27 Mar
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How the public reacted

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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