{"id":"W2576190658","doi":"10.1177/1468794116682823","title":"A sociogram is worth a thousand words: proposing a method for the visual analysis of narrative data","year":2017,"lang":"en","type":"article","venue":"Qualitative Research","topic":"Participatory Visual Research Methods","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Sherbrooke; Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Narrative; Computer science; Visualization; Data science; Narrative network; Data visualization; Qualitative property; Narrative inquiry; Identification (biology); Social network analysis; Graph; Narrative structure; Narrative criticism; Artificial intelligence; World Wide Web; Social media; Theoretical computer science; Machine learning; Linguistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01059075,0.001134787,0.0006886439,0.007551782,0.003207216,0.01201683,0.001944029,0.001680616,0.01074676],"category_scores_gemma":[0.03147682,0.0008056305,0.0014273,0.004188092,0.008265576,0.01311481,0.005998933,0.002656396,0.002354013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001921962,"about_ca_system_score_gemma":0.003261499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002460415,"about_ca_topic_score_gemma":0.003499106,"domain_scores_codex":[0.9923793,0.005501511,0.0003390991,0.0008105686,0.000800605,0.0001689716],"domain_scores_gemma":[0.9802775,0.01389981,0.001096135,0.002281749,0.001801698,0.0006430817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001711743,0.00006310159,0.001808344,0.0009157246,0.00007553669,0.0005027547,0.1040674,0.002123273,0.005090559,0.6911795,0.01684584,0.1771568],"study_design_scores_gemma":[0.00006473641,0.00007688093,0.001129119,0.001081564,0.00005371978,0.0006765735,0.04009676,0.01991643,0.003286213,0.6562043,0.2772721,0.0001415773],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007837971,0.0003776405,0.9711278,0.003897811,0.0003800658,0.0005173717,0.0005664324,0.0009044143,0.01439047],"genre_scores_gemma":[0.07194647,0.0004204424,0.9196165,0.0004814269,0.0001619344,0.0013783,0.0003887958,0.0005477903,0.005058346],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01201683,"threshold_uncertainty_score":0.05600989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9278203283948669,"score_gpt":0.8422690525012019,"score_spread":0.08555127589366507,"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."}}