{"id":"W4366825750","doi":"10.1177/26349825231163140","title":"Problems with quantitative categorization: An argument for qualitative approaches","year":2023,"lang":"en","type":"article","venue":"Environment and Planning F","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Categorization; Positivism; Epistemology; Argument (complex analysis); Data science; Qualitative research; Qualitative property; Computer science; Sociology; Management science; Artificial intelligence; Social science; Machine learning; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0009236245,0.00007258797,0.00009278301,0.00006766453,0.0006300182,0.00004634156,0.00004538668,0.00003115588,0.000008810171],"category_scores_gemma":[0.00002247991,0.00005870885,0.00001278225,0.0001287159,0.0001714412,0.0002317621,0.00001383719,0.00003097019,0.00001614182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001841437,"about_ca_system_score_gemma":0.00001009263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009071569,"about_ca_topic_score_gemma":0.0000400536,"domain_scores_codex":[0.9992946,0.00008417817,0.0001192462,0.0001299908,0.0002024179,0.0001695889],"domain_scores_gemma":[0.9996375,0.0001719346,0.00008163678,0.0000501769,0.00001359832,0.00004515235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001719199,0.00001295284,0.01630504,0.00002972119,0.00004699111,4.502162e-7,0.9113707,0.002797788,0.000004203789,0.06876089,0.0003133294,0.000340755],"study_design_scores_gemma":[0.0003631932,0.0002707083,0.01746143,0.00003071503,0.00001676949,2.601431e-7,0.9339274,0.001129309,0.00000765735,0.003466171,0.04314219,0.0001842413],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9312017,0.0005073309,0.04264874,0.002910227,0.0002347924,0.002464999,0.00005410108,0.0002910914,0.019687],"genre_scores_gemma":[0.9957978,0.00005885552,0.002293087,0.00002140538,0.00005626849,0.0002633261,0.0001015213,0.000006572369,0.00140123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06529472,"threshold_uncertainty_score":0.4845655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1901456056170777,"score_gpt":0.3510546790703302,"score_spread":0.1609090734532525,"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."}}