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

Topic

Oranga Tamariki Leadership Changes

4 items · 3 aliases · peaked week of 24 May 2026 · first seen 13 May 2026

The New Zealand government reports a 14 percent reduction in reported harm in state care residences since 2024, attributing the improvement to enhanced staff training, leadership, and new safety practices like the use of transparent bags.

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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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.

waatea Government / N-A

a pivotal shift marking industry maturity and continuity

#culture: Ngā Aho Whakaari Leadership Change Signals New Chapter for Māori Screen Industry

27 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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