{"id":"W2295376133","doi":"10.2501/jar-2015-006","title":"Accounting for Social-Desirability Bias in Survey Sampling","year":2015,"lang":"en","type":"article","venue":"Journal of Advertising Research","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Advantage Forensics (Canada)","funders":"","keywords":"Social desirability; Accounting; Sampling (signal processing); Social desirability bias; Survey research; Business; Reporting bias; Marketing; Psychology; Social psychology; Political science; MEDLINE; Computer science; Business administration; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.0784379,0.00009893085,0.0004062312,0.0005257816,0.0001798343,0.0001327144,0.0003024221,0.000121472,0.0000054096],"category_scores_gemma":[0.1270383,0.00008618097,0.0001084656,0.0006119648,0.00008633058,0.0003003607,0.0000683528,0.0006008325,0.000002122885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000441605,"about_ca_system_score_gemma":0.0004476677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002952352,"about_ca_topic_score_gemma":0.0001518639,"domain_scores_codex":[0.9962991,0.000973399,0.001276325,0.0001496482,0.0009004004,0.0004011093],"domain_scores_gemma":[0.9865317,0.009466498,0.0007211439,0.0001675896,0.003001939,0.0001111118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001623283,0.0008486798,0.883852,0.0007376543,0.00009239181,0.00001989779,0.008312438,0.0003593185,0.002220508,0.002207206,0.02833327,0.07139338],"study_design_scores_gemma":[0.001982853,0.0004284532,0.4148106,0.0008253676,0.00001473134,0.00004116319,0.00169419,0.002246952,0.004230944,0.5726693,0.0007457055,0.000309813],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9236098,0.00008366675,0.07544386,0.0003118742,0.0001308302,0.0002170663,0.000006071795,0.00003092307,0.0001659356],"genre_scores_gemma":[0.9137856,0.00000654333,0.08594173,0.00001167162,0.0001792918,0.000005380376,0.00000242956,0.00002518301,0.00004220889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.570462,"threshold_uncertainty_score":0.9489421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8263005776308638,"score_gpt":0.5848368616876762,"score_spread":0.2414637159431876,"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."}}