Compare GDP per capita between OECD and non-OECD high-income countries

Compare GDP per capita between OECD and non-OECD high-income countries

Task conventions: Use the frozen country polygons and World Bank NY.GDP.PCAP.CD 2023 column, in current USD per capita. These are country-level indicators, not a subnational surface or a new regional aggregation. Join the supplied ISO_A3 to Country Code exactly. Nonmatching identifiers and missing measurements remain unknown; do not guess them or substitute another year. Retain every original country feature in the declared geography and its benchmark_row_id, including unknowns. No data must have a distinct map category, not zero. Create a quantitative choropleth with five quantile classes (fewer only if tied values collapse breaks), a visible legend with numeric bounds and units, and a neutral No data category. Values equal to a class break enter the upper class. Preserve negative and genuine zero values. This fixed classification and year are disclosed evaluation conventions; do not retrieve live replacements. Count original boundary features, not deduplicated sovereign states; preserve all source rows that meet the declared geography. Country-code sentinels such as -99 remain unmatched. Geography is fixed to original country features with INCOME_GRP in ["1. High income: OECD", "2. High income: nonOECD"]; retain all matching source geometries, and no others. Classification is calculated only over this geography. Membership reflects this disclosed benchmark edition, not current organization membership. Also compare unweighted means of known original country features by these fixed INCOME_GRP groups: {"OECD": ["1. High income: OECD"], "non_OECD": ["2. High income: nonOECD"]}. Do not treat missing values as zero. These are country comparisons, not basin-clipped or population-weighted estimates.



Add the resulting quantitative country layer to the map and retain an inspectable data artifact containing the original country geometry, benchmark_row_id, numeric value and class. End with one fenced JSON object: {count: countries with a known numeric value, unknown_count: countries without one, coverage_note: string, selection: {collectionId, itemId, assetKey}, value_field: numeric_column_name, class_field: classification_column_name, map_layer_id: delivered_layer_id}. The artifact must include known AND unknown countries, not only the known subset. Explain the year, units, key limitations and legend in the final response. Include a metrics object in the final JSON with group-name keys and their numeric means (or null if no known members), and explain the comparison.

Delivery format: provide the answer object with all fields specified above as final_response on assess_result, alongside the inspected final artifact_refs. This replaces the JSON-code-block formatting requirement above. Blue attaches your explicit selection to the accepted final answer. Finish with a concise ordinary-language answer agreeing with that selected result; do not duplicate the JSON in chat.

Supplied immutable inputs:
[
  {
    "name": "World Bank country boundaries",
    "edition": "GeoBenchX harmonized names",
    "units": {},
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  },
  {
    "name": "GDP per capita",
    "edition": "Frozen WDI; current US dollars by year",
    "units": {
      "2023": "current USD per capita",
      "2020": "current USD per capita",
      "2022": "current USD per capita"
    },
    "collectionId": "blue-generated--[resource id withheld]",
    "itemId": "[resource id withheld]",
    "assetKey": "data"
  }
]

{
  "expectedCount": 54,
  "actualCount": 54,
  "expectedMetrics": {
    "OECD": 53000.95120822906,
    "non_OECD": 36194.99632695085
  },
  "actualMetrics": {
    "OECD": 53000.95120822907,
    "non_OECD": 36194.996326950844
  },
  "computationCorrect": true,
  "answerFulfilled": true,
  "adjudication": null,
  "qualification": null,
  "reasons": []
}

Does the full fixed high-income geography support the required exact GDP join, quantile choropleth, and OECD versus non-OECD mean comparison without dropping unknown country rows?

The full fixed geography trial answered the method question. Filtering by the two requested INCOME_GRP values returned 85 original country features. The exact left join on ISO_A3 to Country Code preserved all 85 rows, matched 73 features, left 12 unmatched input features, and produced 54 known 2023 GDP per capita values with 31 unknown values after also counting missing measurements. The classification produced five quantile classes plus class 0 for No data, with class counts 11, 11, 10, 9, 13 and 31 No data. The grouped means were 53000.95120822907 current USD per capita for OECD and 36194.996326950844 for non-OECD using known values only.

The final comparison table is sufficient. OECD has the higher unweighted mean 2023 GDP per capita at 53000.95120822907 current USD per capita versus 36194.996326950844 for non-OECD. The comparison preserves original feature counts and excludes unknown GDP values from the means.

The final result is sufficient. The delivered country layer retains all 85 fixed benchmark high-income country features with original geometry and benchmark_row_id, joins the frozen World Bank NY.GDP.PCAP.CD 2023 values by exact ISO_A3 to Country Code, and keeps 31 unknown values in a distinct No data class rather than zero. The choropleth uses five quantile classes with breaks at 28247.022632872442, 34711.08078293472, 50330.593046729635 and 62536.7320298151 current USD per capita, and the map layer is available on the current map. The paired comparison shows a higher unweighted mean for OECD (53000.95120822907) than for non-OECD (36194.996326950844).

The final result is sufficient. The delivered country layer retains all 85 fixed benchmark high-income country features with original geometry and benchmark_row_id, joins the frozen World Bank NY.GDP.PCAP.CD 2023 values by exact ISO_A3 to Country Code, and keeps 31 unknown values in a distinct No data class rather than zero. The choropleth uses five quantile classes with breaks at 28247.022632872442, 34711.08078293472, 50330.593046729635 and 62536.7320298151 current USD per capita, and the map layer is available on the current map. The paired comparison shows a higher unweighted mean for OECD (53000.95120822907) than for non-OECD (36194.996326950844).