{"id":"W2405005405","doi":"10.1016/j.im.2016.03.003","title":"A pragmatic multi-method investigation of discrepant technological events: Coping, attributions, and ‘accidental’ learning","year":2016,"lang":"en","type":"article","venue":"Information & Management","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Disengagement theory; Attribution; Coping (psychology); Psychology; Accidental; Social psychology; Cognitive psychology; Psychotherapist","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001520957,0.00008358658,0.0001141712,0.0002342218,0.0003132024,0.00006081109,0.0001628429,0.00005488728,0.00007594491],"category_scores_gemma":[0.0003356416,0.00006308429,0.00003336426,0.0002805369,0.0001330549,0.001190153,0.0002252815,0.00006026798,0.00007597944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001073197,"about_ca_system_score_gemma":0.00001154693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006163034,"about_ca_topic_score_gemma":0.0000435902,"domain_scores_codex":[0.9988965,0.0001467709,0.0003812712,0.0001054258,0.0002882262,0.0001818027],"domain_scores_gemma":[0.9994354,0.00007874204,0.0002548359,0.0001114092,0.00007041348,0.00004925544],"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":[0.0000131689,0.00004410026,0.08253703,0.00029525,0.0001155879,0.000001185445,0.008656701,0.00004849456,0.00008680297,0.4874625,0.0007979585,0.4199412],"study_design_scores_gemma":[0.00489018,0.0001552643,0.4156347,0.001656195,0.0002815312,0.000002679879,0.05383909,0.006141067,0.0006331056,0.03460293,0.4812071,0.0009561114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1039829,0.00008753105,0.862309,0.004386932,0.0002021672,0.001666517,0.000006528039,0.0004467627,0.0269116],"genre_scores_gemma":[0.981487,0.0003074923,0.0162952,0.00007650629,0.00001638486,0.00008354345,0.00001942022,0.000004072519,0.001710415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8775041,"threshold_uncertainty_score":0.2572503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02339298306617515,"score_gpt":0.3142637303825909,"score_spread":0.2908707473164158,"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."}}