{"id":"W2144051761","doi":"10.1007/s12208-012-0093-1","title":"Scale development research in nonprofit management & marketing: a content analysis and recommendation for best practices","year":2012,"lang":"en","type":"article","venue":"International Review on Public and Nonprofit Marketing","topic":"Nonprofit Sector and Volunteering","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Conceptualization; Construct (python library); Scale (ratio); Content analysis; Variety (cybernetics); Best practice; Variance (accounting); Marketing; Knowledge management; Business; Computer science; Sociology; Management","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":[],"category_scores_codex":[0.03760005,0.000172979,0.0003116312,0.0006450411,0.0005680436,0.0002748669,0.0002650068,0.00008016675,0.000334685],"category_scores_gemma":[0.004435186,0.0001475548,0.00008042511,0.00086448,0.0001081702,0.0006858815,0.0002089047,0.0002579326,0.00001875616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003453536,"about_ca_system_score_gemma":0.00007170902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005833761,"about_ca_topic_score_gemma":0.001955849,"domain_scores_codex":[0.9964077,0.001221582,0.0005834584,0.0004644418,0.0006963022,0.0006265242],"domain_scores_gemma":[0.9965441,0.002293602,0.0004137161,0.0001437742,0.0003898434,0.0002149395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001463973,0.0001237946,0.5125058,0.0007626892,0.0002149197,6.873564e-7,0.0006208026,5.573449e-8,0.00001593855,0.001533021,0.0005124867,0.4835634],"study_design_scores_gemma":[0.0003801156,0.0000170602,0.28498,0.001631763,0.00009007376,0.000001993743,0.002940155,0.00006517713,0.00001199944,0.00003096207,0.7096161,0.0002346029],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.794876,0.01116073,0.001545777,0.04281448,0.000961288,0.003774136,0.00002594472,0.00008456718,0.1447571],"genre_scores_gemma":[0.9448154,0.03423911,0.01128249,0.0007499694,0.0004581261,0.0009787831,0.0001294603,0.00003009366,0.007316544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7091036,"threshold_uncertainty_score":0.9909933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3401818766374567,"score_gpt":0.4770565742639941,"score_spread":0.1368746976265374,"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."}}