{"id":"W2200746473","doi":"","title":"Technology and storytelling: Usages for professional development in police learning","year":2010,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Policing Practices and Perceptions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University; Royal Roads University","funders":"","keywords":"Storytelling; Professional development; Sociology; Pedagogy; Public relations; Narrative; Political science; Linguistics","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":[0.001175158,0.000200899,0.0002467335,0.000358107,0.0009523644,0.0001506901,0.0001698892,0.0002463717,0.0002423047],"category_scores_gemma":[0.0001715795,0.0002147832,0.00001965069,0.000566382,0.0002330925,0.0002784007,0.00005348552,0.001374211,0.00001669551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003106669,"about_ca_system_score_gemma":0.001306023,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01298531,"about_ca_topic_score_gemma":0.09063269,"domain_scores_codex":[0.9979349,0.0003337921,0.00037218,0.0004861265,0.0003850359,0.0004879592],"domain_scores_gemma":[0.9986828,0.0003418992,0.0005095002,0.0001328371,0.000130523,0.0002024613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001087616,0.0003096061,0.5900087,0.0001085403,0.000009057992,6.390645e-7,0.02788328,0.00002256338,0.0005664596,0.2869639,0.0003456739,0.09367288],"study_design_scores_gemma":[0.0003638671,0.0001308432,0.4417263,0.000247403,0.000006064664,0.000001308015,0.01189201,0.00008440007,0.0000249616,0.002504891,0.5427448,0.0002731734],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9525352,0.0001310014,0.00001352822,0.02715307,0.00136807,0.0006149724,0.000003312723,0.00008686971,0.01809402],"genre_scores_gemma":[0.9107994,0.0005881517,0.001058146,0.0004888682,0.0002483111,0.0001977079,0.00001497763,0.00002172398,0.08658268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.542399,"threshold_uncertainty_score":0.9935873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1059130040240187,"score_gpt":0.381394580919595,"score_spread":0.2754815768955763,"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."}}