{"id":"W4243103789","doi":"10.33423/jhetp.v20i15.3939","title":"Using Criteria of Significance to Make Sense of Data: Implications for Qualitative Research","year":2020,"lang":"en","type":"article","venue":"Journal of Higher Education Theory and Practice","topic":"Qualitative Research Methods and Applications","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Construct (python library); Qualitative research; Qualitative property; Context (archaeology); Interpretation (philosophy); Computer science; Set (abstract data type); Value (mathematics); Psychology; Task (project management); Data science; Engineering; Sociology; Social science; Machine learning","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":[0.03076204,0.00004671121,0.0001666525,0.0001051972,0.000269989,0.00004241484,0.0002644075,0.0000350445,0.00006484007],"category_scores_gemma":[0.02247693,0.00004211444,0.00003161879,0.0005990349,0.0003859129,0.00060563,0.00004900439,0.0001609075,9.674112e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003462642,"about_ca_system_score_gemma":0.001081445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001079971,"about_ca_topic_score_gemma":0.000003396807,"domain_scores_codex":[0.9894407,0.009569767,0.0004171038,0.0001427753,0.0002996834,0.0001299809],"domain_scores_gemma":[0.9676031,0.02881427,0.0005353171,0.0001805293,0.002674271,0.000192473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006221118,0.000188907,0.00001163503,0.00006581537,0.00004374147,9.105892e-8,0.09427913,0.000002156792,0.04136921,0.8522689,0.004090607,0.007057745],"study_design_scores_gemma":[0.0001699499,0.0002675861,0.0005453542,0.00005528846,0.0000637684,0.000003350816,0.2472865,0.000003562947,0.000993977,0.285965,0.4645753,0.00007040338],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.08827258,0.004220976,0.3805764,0.5095348,0.0004172653,0.002046674,0.0006204268,0.0000108634,0.01430003],"genre_scores_gemma":[0.687397,0.0002739416,0.3103097,0.000837951,0.0005543008,0.00002607826,0.000004985097,0.000009758239,0.0005862499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5991244,"threshold_uncertainty_score":0.9980344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7963732700863477,"score_gpt":0.7607477859730241,"score_spread":0.03562548411332367,"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."}}