{"id":"W2089229856","doi":"10.1080/13645579.2012.661207","title":"Institutional ethnography and data analysis: making sense of data dialogues","year":2012,"lang":"en","type":"article","venue":"International Journal of Social Research Methodology","topic":"Qualitative Research Methods and Ethics","field":"Social Sciences","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Hort Innovation","keywords":"Active listening; Ethnography; Sociology; Qualitative research; Qualitative property; Data collection; Social research; Epistemology; Interpretative phenomenological analysis; Data science; Social science; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch"],"domain":"methods","study_design":"qualitative","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1710885,0.0000893854,0.0004455798,0.001387182,0.0005479528,0.00009126258,0.002272394,0.0002132791,0.0001318378],"category_scores_gemma":[0.06181019,0.00007900073,0.0001284349,0.001212431,0.004673148,0.00147612,0.001593346,0.001075472,0.000002457761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001131623,"about_ca_system_score_gemma":0.0009886767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329344,"about_ca_topic_score_gemma":0.0007720691,"domain_scores_codex":[0.9672212,0.02828132,0.0006957079,0.0002753641,0.002969228,0.0005571694],"domain_scores_gemma":[0.9748468,0.02110492,0.0004720639,0.0003532306,0.002996778,0.0002261928],"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":[0.0006749938,0.0003240218,0.02602999,0.00004437688,0.004518171,0.00006647298,0.1082387,0.000007126346,0.001499235,0.7357166,0.002611883,0.1202684],"study_design_scores_gemma":[0.001779371,0.0003405483,0.125953,0.0001908334,0.000772886,0.00008718466,0.1525568,0.0005726087,0.0002275075,0.2705026,0.4464979,0.0005187646],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2751613,0.01180243,0.6200364,0.07057191,0.003597724,0.0005418896,0.001765096,0.00003273351,0.01649059],"genre_scores_gemma":[0.7555283,0.002203115,0.2397848,0.0001069403,0.002251204,0.000001675318,0.00006884477,0.000007879483,0.00004724081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.480367,"threshold_uncertainty_score":0.9980356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9454986453943374,"score_gpt":0.7607215828876077,"score_spread":0.1847770625067297,"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."}}