{"id":"W2253760496","doi":"10.1515/2152-2812.1084","title":"Gain and Loss Domains and the Choice of Welfare Measure of Positive and Negative Changes","year":2012,"lang":"en","type":"article","venue":"Journal of Benefit-Cost Analysis","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Measure (data warehouse); Equivalence (formal languages); Compensation (psychology); Willingness to accept; Economics; Welfare; Willingness to pay; Econometrics; Value (mathematics); Microeconomics; Public economics; Mathematics; Computer science; Statistics; Psychology; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01888922,0.0008608896,0.0009768603,0.003601434,0.0007948769,0.005000773,0.001016179,0.001587428,0.003593379],"category_scores_gemma":[0.0460872,0.0002699945,0.001057485,0.001927535,0.008547708,0.009709843,0.00312531,0.002551696,0.0003626953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00169093,"about_ca_system_score_gemma":0.0005566415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006340678,"about_ca_topic_score_gemma":0.0005893023,"domain_scores_codex":[0.9923441,0.00531547,0.000349767,0.0004213962,0.001200218,0.0003689724],"domain_scores_gemma":[0.9789342,0.01631719,0.001333184,0.001327265,0.001270064,0.0008181263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007755687,0.0003459028,0.01327514,0.0002974135,0.0001965305,0.0002663755,0.0008093048,0.0235912,0.00178128,0.8411854,0.002645113,0.1148308],"study_design_scores_gemma":[0.00004522685,0.0002938204,0.01594899,0.0003529419,0.00006633103,0.0003286908,0.001292319,0.02741869,0.001033126,0.9474176,0.00572648,0.00007582195],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5230928,0.005041878,0.3412459,0.01051459,0.0006072158,0.0002889112,0.0009178606,0.0001677323,0.1181231],"genre_scores_gemma":[0.9799491,0.0006467946,0.01753566,0.0002514998,0.0001043254,0.0001190899,0.0001522293,0.00002686051,0.001214393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01888922,"threshold_uncertainty_score":0.09989691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04145325732786882,"score_gpt":0.2249491793213695,"score_spread":0.1834959219935006,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}