{"id":"W197622962","doi":"10.3138/cjpe.16.006","title":"Softly, Softly Catch the Monkey: Innovative Approaches to Measure Socially Sensitive and Complex Issues in Evaluation Research","year":2001,"lang":"en","type":"article","venue":"Canadian Journal of Program Evaluation","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Respondent; Reliability (semiconductor); Measure (data warehouse); Psychology; Government (linguistics); Focus (optics); Research design; Management science; Knowledge management; Computer science; Data science; Applied psychology; Sociology; Engineering; Political science; Social science; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3752055,0.002095821,0.002069596,0.01255402,0.007656565,0.01766637,0.003801754,0.004388922,0.00387067],"category_scores_gemma":[0.4703885,0.001880185,0.002498304,0.009013824,0.03814803,0.02412595,0.01924396,0.009382343,0.0006606131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01119982,"about_ca_system_score_gemma":0.01529686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001513003,"about_ca_topic_score_gemma":0.004544233,"domain_scores_codex":[0.4292643,0.5067607,0.01561286,0.005836499,0.04062795,0.001897687],"domain_scores_gemma":[0.3243181,0.5727575,0.02796962,0.04126421,0.03112045,0.002570032],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002513105,0.0008660225,0.01217164,0.005067789,0.0005863282,0.0002340426,0.09756332,0.003311527,0.002512647,0.3500192,0.006083333,0.5213327],"study_design_scores_gemma":[0.0004979802,0.001542359,0.01657918,0.01123245,0.0007827072,0.0007969544,0.06436501,0.02181686,0.00805583,0.8151674,0.05841804,0.000745245],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03343506,0.001821754,0.9149211,0.02304629,0.0004367881,0.005576513,0.000065107,0.0003099177,0.02038749],"genre_scores_gemma":[0.2393558,0.0008830964,0.741143,0.002375162,0.0001621787,0.01492777,0.00003152541,0.0001112957,0.001010117],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6247945,"threshold_uncertainty_score":0.7704829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8765369178333454,"score_gpt":0.6071075175501194,"score_spread":0.269429400283226,"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."}}