{"id":"W4411459860","doi":"10.1177/20531680251351238","title":"Changing the lens: The contingency of results from conjoint experiments on the outcome variable and the estimand","year":2025,"lang":"en","type":"article","venue":"Research & Politics","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Contingency; Outcome (game theory); Conjoint analysis; Psychology; Variable (mathematics); Econometrics; Positive economics; Social psychology; Economics; Epistemology; Microeconomics; Preference; Mathematics","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1970353,0.002250518,0.003848687,0.007184027,0.004369979,0.01863475,0.003489783,0.004389524,0.009862853],"category_scores_gemma":[0.4145375,0.001582347,0.002175177,0.005163681,0.03316995,0.02146441,0.01126541,0.01654115,0.001271495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007074717,"about_ca_system_score_gemma":0.006918589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003127538,"about_ca_topic_score_gemma":0.004119913,"domain_scores_codex":[0.753138,0.2061502,0.005762502,0.009212989,0.02470624,0.001029997],"domain_scores_gemma":[0.3900242,0.5280655,0.0173281,0.04752272,0.0152617,0.001797731],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009465154,0.0002431397,0.008059517,0.002598222,0.000934824,0.0004735041,0.01320629,0.001526511,0.002552735,0.7995083,0.01407197,0.1558783],"study_design_scores_gemma":[0.0001906169,0.0005261791,0.006012731,0.00192949,0.0005327142,0.0004467899,0.007074706,0.005217248,0.003480246,0.9168519,0.0575377,0.0001997046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04113934,0.02534258,0.6760722,0.1598416,0.01083994,0.0008924556,0.002101106,0.0009277256,0.08284304],"genre_scores_gemma":[0.4925333,0.01030967,0.4493623,0.03168752,0.005814839,0.002734971,0.0004517431,0.0007227311,0.006382777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8029647,"threshold_uncertainty_score":0.9901984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2528790355996412,"score_gpt":0.4911974684037916,"score_spread":0.2383184328041504,"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."}}