{"id":"W2507236586","doi":"10.1016/j.evalprogplan.2016.08.005","title":"The use of Outcome Harvesting in learning-oriented and collaborative inquiry approaches to evaluation: An example from Calgary, Alberta","year":2016,"lang":"en","type":"article","venue":"Evaluation and Program Planning","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"University of Toronto; United Way","keywords":"Neighbourhood (mathematics); Outcome (game theory); Work (physics); Collaborative learning; Process (computing); Community development; Knowledge management; Sociology; Public relations; Engineering; Computer science; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.04446481,0.000603693,0.0009173441,0.00412707,0.0199727,0.01471241,0.004242959,0.003052562,0.003149088],"category_scores_gemma":[0.03195347,0.0005727032,0.0006499388,0.008105272,0.01563196,0.002784532,0.008505606,0.003777963,0.0003381556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07359277,"about_ca_system_score_gemma":0.1318334,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.884594,"about_ca_topic_score_gemma":0.9595578,"domain_scores_codex":[0.97078,0.01816251,0.0007306049,0.0009622065,0.006311376,0.00305341],"domain_scores_gemma":[0.946346,0.03665946,0.0008083702,0.003003097,0.0102873,0.002895632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0007924507,0.001035268,0.03532976,0.001093962,0.0001461383,0.002988078,0.1165502,0.008727559,0.003756205,0.2504711,0.01767113,0.5614381],"study_design_scores_gemma":[0.0007300504,0.001396742,0.1287892,0.003012496,0.0005391953,0.001163263,0.308524,0.01572301,0.009670158,0.1663406,0.3634171,0.0006941792],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3395243,0.006565087,0.0807158,0.03788189,0.0004395235,0.002691232,0.0003933612,0.0006576902,0.531131],"genre_scores_gemma":[0.9144945,0.002064134,0.05189842,0.001618445,0.00004034159,0.0005090405,0.0001048451,0.0001808152,0.02908941],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.115406,"threshold_uncertainty_score":0.5339555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7616272255532968,"score_gpt":0.5431760229740711,"score_spread":0.2184512025792257,"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."}}