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Grant-application essentials — child poverty

For Lisa, tilskuddsansvarlig

Grant-application essentials — child poverty

The task
Writing a child-poverty grant application that names a kommune, backs the claim with real numbers, and survives a fact-check by a directorate's reviewer.
A focused starter set for grant applications about child poverty at kommune resolution. Ordered from headline → ground truth → temporal depth → lived-experience proxy → Atlas synthesis. Together these five datasets answer the four questions every directorate reviewer asks: how many, how persistent, how that compares to the neighbours, and what the policy gap looks like. Every dataset here is at kommune (4-digit kommune_code, post-2020 reform) resolution. They share a join key — `kommune_code` — so a single query stitches the whole evidence base together.

Datasets in this collection

  1. 1
    Barne-, ungdoms- og familiedirektoratet logo
    Barnefattigdom kommunemonitor
    Barne-, ungdoms- og familiedirektoratet · 💰 Income & poverty
    Stable
    The headline indicator most directorates already cite. Bufdir's Barnefattigdom kommunemonitor is the standard reference for "how many children live in low-income households in this kommune".
  2. 2
    The SSB ground truth. Bufdir's monitor is derived from this table. Cite SSB when a reviewer wants the canonical source; cite Bufdir when you want the editorial framing.
  3. 3
    Persistent low-income (3-year average, EU-60 scale). The difference between *transient* and *persistent* poverty is the difference between a household between jobs and a household stuck. Reviewers read persistence as a stronger evidence base.
  4. 4
    Folkehelseinstituttet logo
    Trangbodd_UTDANN
    Folkehelseinstituttet · 🎓 Education & youth
    Stable
    A lived-experience proxy: children in overcrowded housing. Closely correlates with low income but adds the "what does poverty feel like" dimension that grant narratives need. Pairs well with the income tables above.
  5. 5
    The Atlas synthesis view. Combines Bufdir's monitor with SSB's coverage to surface the kommuner where Bufdir didn't publish and where, if your application is about underserved data, you have a story to tell.

How to use these together

All five datasets join on kommune_code — the 4-digit post-2020 kommune identifier. A minimal query that pulls a single kommune's evidence base looks like this (PostgREST):

curl -sS 'https://api-atlas.sovereignsky.no/indicator_summary?kommune_code=eq.3024&select=kommune_name,indicator_id,latest_value,latest_year'

To compare a kommune against its neighbours in the same fylke, swap eq.3024 for like.30* (the 2-digit fylke prefix). The four upstream tables are also queryable directly via PostgREST — use those when you need the raw structure (publisher dimensions, units, etc.) rather than the indicator framing.

Watch out: name-based kommune joins multiply rows ~5× because pre-2020 kommune codes still appear in some upstream history. Always join on kommune_code and filter is_active = true when joining against dim_kommune.