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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
live window
Press topic

Ai Ethics In Healthcare

2 articles · 2 aliases in press · peaked week of 3 May 2026 · first seen 8 May 2026

AI sign language avatars are advancing rapidly, sparking concerns about accuracy, cultural disrespect, and the erosion of Deaf language rights.

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 2 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.

stuff Centre-left

innovative but cautious integration of ai

He couldn’t talk about depression so he developed an AI ‘companion’
26 Jan
nzherald Centre-right

technology risks undermining cultural trust

AI sign language avatars raise accuracy and ethics fears for Deaf users
6 May
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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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