{"id":"W3081349205","doi":"10.1016/j.lisr.2020.101037","title":"Writing-up ethnographic research as a thematic narrative: The excerpt-commentary-unit","year":2020,"lang":"en","type":"article","venue":"Library & Information Science Research","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Qualitative research; Citation; Interview; Ethnography; Publication; Focus group; Thematic analysis; Scopus; Sociology; Library science; Unit (ring theory); Psychology; Social science; Political science; Computer science; MEDLINE; Mathematics education","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004689428,0.0006924859,0.0004212437,0.001673929,0.007775833,0.004741542,0.001195993,0.002664258,0.01289508],"category_scores_gemma":[0.02026002,0.0002578313,0.0003641557,0.002149725,0.005583162,0.002516593,0.003361034,0.005449029,0.002621073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003751584,"about_ca_system_score_gemma":0.003895239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005836327,"about_ca_topic_score_gemma":0.01281327,"domain_scores_codex":[0.9942943,0.004156453,0.0001698975,0.0003159918,0.0006594124,0.000403938],"domain_scores_gemma":[0.9760686,0.0201217,0.000506503,0.0005777752,0.00209884,0.0006265139],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001750581,0.00007624484,0.0004182443,0.001134615,0.00001110456,0.002495179,0.6549766,0.0001087501,0.008767379,0.05705446,0.2486435,0.02613885],"study_design_scores_gemma":[0.00001497226,0.00004080127,0.001082552,0.000996745,0.00001158744,0.0008391288,0.3348081,0.0001544075,0.003488329,0.005586758,0.6529471,0.0000294957],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.1418676,0.005992827,0.04995005,0.2116272,0.05885853,0.003644083,0.003465025,0.0007381524,0.5238565],"genre_scores_gemma":[0.7169337,0.003501915,0.01985903,0.04538473,0.01095311,0.003517532,0.001534796,0.001246361,0.1970688],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9953105,"threshold_uncertainty_score":0.04313833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1953013319405041,"score_gpt":0.4514792237247321,"score_spread":0.256177891784228,"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."}}