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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.
Rolling 7 days is a sliding live window for “current vibes”; switch to Weekly to compare specific weeks side-by-side.
Weekly Rolling 7 days
←
Week of 8 Jun 2026
→ This week
Press topic

Medical Registration Transparency

1 articles · 1 aliases in press · first seen 17 May 2026

The article exposes a growing trend of fake New Zealand doctors using social media and AI-generated content to promote unapproved weight loss products, often falsely claiming medical endorsement or local production, while highlighting the risks to public health and trust in the医疗

Coverage by outlet lean Methodology →

Stacked weekly counts; colour by editorial lean. Stuff and The Spinoff lean centre-left, NZ Herald centre-right, others centre.

Alias drift

How press outlets have named this topic, week by week.

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Recent headlines

Most recent 1 articles linking to this topic.

Sample framings

Up to 12 framings spread across outlets. Each framing is the LLM's one-line characterisation of the article's editorial angle — not a quote.

rnz Centre

need for public access to verified doctor credentials

Fake new zealand doctors are trying to sell you glp 1 weight loss products
9 Oct
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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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