[
 {"id":"C1","text":"The unadjusted association between training hours and next-year productivity growth is negative: -0.132 pp per hour, 95% CI [-0.160, -0.103].","results_keys":["naive_estimate","naive_ci_low","naive_ci_high"],"status":"supported","caveat":"Association only; confounded by skill_index."},
 {"id":"C2","text":"Adjusting for pre-programme skill_index, one more training hour raises productivity growth by 0.254 pp (robust 95% CI [0.234, 0.273]); conclusion positive_effect.","results_keys":["effect_estimate","effect_se","effect_ci_low","effect_ci_high","conclusion"],"status":"supported","caveat":"Causal only under selection on observables with skill_index as the sole confounder and linear homogeneous effect."},
 {"id":"C3","text":"The sign reversal is explained by confounding: skill_index is positively correlated with training hours and has a strongly negative coefficient on growth.","results_keys":["corr_skill_hours","skill_index_coefficient"],"status":"supported","caveat":"Mechanical omitted-variable-bias decomposition, not a test of the full causal structure."},
 {"id":"C4","text":"The adjusted model fits much better than the baseline (RMSE 1.976 vs 3.860 pp).","results_keys":["model_metric","baseline_metric"],"status":"supported","caveat":"In-sample fit; better fit does not by itself validate causal identification."},
 {"id":"C5","text":"The estimate is robust to including the 12 negative-hours rows and to adding skill^2; no evidence of interaction or curvature in hours.","results_keys":["sensitivity_all_rows_estimate","sensitivity_quad_skill_estimate","diag_interaction_pvalue","diag_hours_sq_pvalue"],"status":"supported","caveat":"Limited set of specification checks; unobserved confounding untestable."},
 {"id":"C6","text":"12 rows with impossible negative training hours were excluded, leaving 1188 of 1200 firms analysed.","results_keys":["n_analysed","n_input_rows","data_issues"],"status":"supported","caveat":"Cause of negative values unknown."}
]