Task card — F6-dev-01
- Family / split: F6 Integrated mini-projects / development
- Question: Does life expectancy rise with ln GDP per capita across countries in the most recent usable World Bank year? Estimand = cross-country OLS slope (years per log-point), HC-robust uncertainty; full chain question → audit → baseline → method → results → uncertainty → failure discussion → figure + table → report.
- Data type: observed (World Bank WDI, NY.GDP.PCAP.PP.KD and SP.DYN.LE00.IN, 2015–2023, retrieved 2026-10-30, CC BY 4.0), 2,349 entity-year rows + 296 entity metadata rows.
- Scope / prerequisites: filtering aggregates vs countries, year-selection rule, missing-value accounting, OLS with HC SE, matplotlib figure, CSV table.
- Allowed information: the two data files and README only.
- Expected artifacts: results.json (19 keys), report.md (6 sections), analysis.py (regenerates results + figure1.png + table1.csv), claims.json, figure1.png, table1.csv.
- Rubric summary: criteria — analysis year and counts exact; slope within 0.02; HC SE within 5%; CI bounds within 0.03; r and R² within 0.005; baseline/model RMSE within 1–1.5%; conclusion code; valid PNG; table ≥ 2 rows. Critical checks — input row counts (fabrication), feasibility must be complete (false completion), conclusion vs CI consistency (invalid inference), year substitution without a data_issues entry (unreported substitution). Baseline key = baseline_metric.
- Oracle provenance: independent_code (
~/wp29-oracles/F6-dev-01/reference.py, numpy from definitions); designer = WP29 builder agent; no human check. - Difficulty rationale: easy–moderate; the care points are the aggregates in the 'all' download, the year rule and counting the missing countries; the statistics are textbook.
- Budget class: benchmark (4.00 USD cap, 25 min wall, 80 turns per session).
- Anticipated failure modes: including regional/income aggregates (n = 241 instead of 197); choosing 2022 because 2023 has two more missing countries; conventional instead of robust SE; forgetting the figure/table; claiming causality.
- Contamination risk: medium — the Preston curve is well known, but the exact 2023-vintage slope, counts and RMSEs cannot be recalled.