{"id":"W3109009690","doi":"10.17351/ests2020.459","title":"Social Dynamics of Expectations and Expertise: AI in Digital Humanitarian Innovation","year":2020,"lang":"en","type":"article","venue":"Engaging Science Technology and Society","topic":"Education, Healthcare and Sociology Research","field":"Psychology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université de Sherbrooke","funders":"Mitacs; Canada Research Chairs","keywords":"Vision; Negotiation; Performative utterance; Dynamics (music); Sociology; Boundary object; Social innovation; Realization (probability); Epistemology; Reflexivity; Public relations; Political science; Knowledge management; Social science; Computer science","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.01305261,0.0003548025,0.0003702535,0.002165909,0.007817471,0.01086685,0.001182017,0.003839812,0.004040322],"category_scores_gemma":[0.03230943,0.0003505061,0.0003550398,0.001073607,0.03407891,0.01256969,0.009077305,0.003521643,0.0003123209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00565316,"about_ca_system_score_gemma":0.003186674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002792196,"about_ca_topic_score_gemma":0.001386885,"domain_scores_codex":[0.986136,0.01028766,0.0003053451,0.0008384408,0.001502435,0.0009301348],"domain_scores_gemma":[0.9660097,0.02500049,0.003527252,0.001169246,0.00168179,0.002611495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007870187,0.00007506884,0.007259575,0.00008022221,0.00002064502,0.0005905979,0.3081572,0.001759185,0.0009293085,0.6709149,0.001253773,0.008880786],"study_design_scores_gemma":[0.00004367538,0.0001009538,0.007104467,0.0002241263,0.00001948194,0.0004635447,0.3003981,0.007478125,0.0006790044,0.6459534,0.03743822,0.00009696621],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6935598,0.0007180551,0.04927603,0.04236729,0.0001479209,0.0000702871,0.00004815873,0.00005583314,0.2137566],"genre_scores_gemma":[0.998833,0.00005225428,0.0004628411,0.0001471719,0.00001267446,0.00001360776,0.000003951149,0.000006115967,0.0004684579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9921826,"threshold_uncertainty_score":0.06902963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05975473557389118,"score_gpt":0.4263929054313248,"score_spread":0.3666381698574336,"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."}}