{"id":"W4312036752","doi":"10.1093/geroni/igac059.2720","title":"THE QUALITY IN QUALITATIVE: AN EXAMINATION OF RETIREMENT INTERVIEWS","year":2022,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Unpacking; Construct (python library); Qualitative research; Narrative; Context (archaeology); Sociology; Qualitative analysis; Qualitative property; Quality (philosophy); Value (mathematics); Psychology; Social psychology; Epistemology; Social science; Computer science; History; Linguistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1655235,0.0005844513,0.0009621823,0.008541617,0.01817008,0.008936819,0.003232517,0.002659252,0.003937288],"category_scores_gemma":[0.2597691,0.001523701,0.0005976619,0.009597497,0.01755222,0.009128156,0.01520014,0.003155936,0.0005395552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02040633,"about_ca_system_score_gemma":0.01520765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02847361,"about_ca_topic_score_gemma":0.03325197,"domain_scores_codex":[0.8411832,0.1361619,0.005243754,0.002966151,0.009604561,0.004840464],"domain_scores_gemma":[0.6278328,0.3173027,0.01789565,0.006684985,0.02658365,0.003700149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001846747,0.000009633984,0.001454711,0.0001149651,0.000001904798,0.00009674887,0.9940043,0.00001939899,0.0001073204,0.00137439,0.0001899506,0.002608158],"study_design_scores_gemma":[0.000003483897,0.00002089768,0.002905049,0.0004359143,0.000003105133,0.0001006408,0.9858297,0.00007973842,0.0001359048,0.0008884841,0.009586029,0.00001102608],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9119117,0.003697395,0.03032892,0.01218293,0.0002960559,0.002702919,0.0009274732,0.0001050878,0.03784758],"genre_scores_gemma":[0.9831263,0.001538738,0.006146095,0.001514998,0.00005688888,0.002526582,0.0002280852,0.0001062039,0.004756178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1655235,"threshold_uncertainty_score":0.8753822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4241312589541227,"score_gpt":0.5464783409329507,"score_spread":0.1223470819788279,"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."}}