uploaded: Full reproducibility metadata for multi-model experiment
Browse files
experiment_config_multimodel.json
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{
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"experiment": "multi-model intersectional bias study",
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"n_observations": 384,
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"methods": [
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"SEAT",
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"CEAT",
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"MLM"
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],
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"datasets": [
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"CareerFamily",
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"CompetenceWarmth",
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"PleasantUnpleasant"
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],
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"pairs": [
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"Hindu_Female",
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"Hindu_Male",
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"LowerCaste_Female",
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"LowerCaste_Male",
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"Muslim_Female",
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"Muslim_Male",
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"UpperCaste_Female",
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"UpperCaste_Male"
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],
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"n_bootstrap_ceat": 3000,
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"ias_threshold": 0.05,
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"within_method_z_normalisation": true,
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"seed": 42,
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"encoder_models": {
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"SEAT": [
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"mpnet-multi",
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"BGE-M3",
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"E5-large",
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"Qwen3-Emb-4B",
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"IndicSBERT",
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"MuRIL"
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],
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"CEAT": [
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"mBERT",
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"MuRIL",
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"ModernBERT",
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"XLM-R-large",
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"IndicBERT-v2"
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],
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"MLM": [
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"mBERT",
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"MuRIL",
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"ModernBERT",
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"XLM-R-large",
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"IndicBERT-v2"
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]
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},
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"ml_models": [
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"Ridge",
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"RandomForest",
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"GradBoosting",
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"ElasticNet",
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"GaussianProcess",
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"MLP"
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],
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"best_ml_model": "Ridge",
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"best_lodo_r2": 0.9405090356483208,
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"best_lomo_r2": 0.9386120562963216,
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"best_lomoo_r2": 0.9377524162718508,
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"cv_axes": {
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"LODO": "3 groups (datasets)",
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"LOMO": "3 groups (methods)",
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"LOMOO": "10 groups (encoder models)"
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},
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"feature_cols_real": [
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"score_A",
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"score_B",
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"abs_score_A",
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"abs_score_B",
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"max_single",
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"score_A_times_B",
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"score_A_sq",
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"score_B_sq"
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],
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"feature_cols_dummy": [
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"dummy_gaussian",
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"dummy_uniform",
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"dummy_permuted_target"
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],
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"hardware": {
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"gpu": "NVIDIA T4 (15 GB VRAM)",
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"ram": "12.7 GB",
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"platform": "Google Colab free tier"
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},
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"key_findings": {
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"linearity": "Ridge (linear) R\u00b2=0.941 beats all non-linear models",
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"career_family_scale_artifact": "CareerFamily LODO R\u00b2 was negative at 72 rows without normalisation; positive (0.72) at 384 rows with z-norm",
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"snr": 53.6,
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"ablation_p": "< 10^-100 for all 6 conditions",
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"muslim_male_lir_only": {
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"IAS": -0.0470513346414766,
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"LIR": 0.0781596722336495
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},
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"encoder_heterogeneity": {
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"easiest": "mBERT (LOMOO R\u00b2=0.983), XLM-R-large (0.985)",
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"hardest": "Qwen3-Emb-4B (0.429), mpnet-multi (0.539)",
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"interpretation": "SEAT-only models encode bias differently from CEAT/MLM models"
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}
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}
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}
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