OpenBrief
⌘K
Log in Sign up
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
Topic

Debt Allocation

5 items · 5 aliases · first seen 11 May 2026

The post criticizes current government debt use, arguing it is disproportionately allocated to tax cuts for landlords and tobacco companies rather than supporting public health or jobs during crises.

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.

Free account Watch this topic with a free account — get alerted when framing shifts, when an MP adopts new language, or when discourse and press diverge. Create a free account Log in

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.

No framings recorded for this topic yet.

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 →

Spotted something wrong on this page? Report a correction.