{"id":"W292912147","doi":"10.3138/cjpe.0023.007","title":"Informing Evaluation Capacity Building Through Profiling Organizational Capacity for Evaluation: An Empirical Examination of four Canadian Federal Government Organizations","year":2009,"lang":"en","type":"article","venue":"Canadian Journal of Program Evaluation","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Organization development; Government (linguistics); Capacity building; Evaluation methods; Knowledge management; Organizational effectiveness; Order (exchange); Business; Organizational performance; Process management; Computer science; Political science; Finance; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03494162,0.0002917699,0.0004447533,0.0008179623,0.0008979317,0.0005133454,0.0006404163,0.0002475207,0.001978971],"category_scores_gemma":[0.02127316,0.0002728158,0.0001524742,0.002283937,0.0001220627,0.002850684,0.00001318753,0.0002868004,0.000008773877],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004065141,"about_ca_system_score_gemma":0.01885653,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003938769,"about_ca_topic_score_gemma":0.1406977,"domain_scores_codex":[0.9890794,0.001361198,0.002039779,0.0004572949,0.006524428,0.000537857],"domain_scores_gemma":[0.9726164,0.0003544785,0.001724888,0.0004452654,0.02412206,0.0007369062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004452928,0.0002519534,0.05707799,0.00002587478,0.0001077155,0.000001446137,0.01110734,0.02997535,0.001108499,0.007622771,0.0007150081,0.8919615],"study_design_scores_gemma":[0.003482548,0.001704852,0.3033331,0.0001155593,0.000540872,0.00007850716,0.003179497,0.6312014,0.003301753,0.04914235,0.003421169,0.0004984108],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9625778,0.0001075314,0.02695463,0.001584575,0.001040256,0.004739477,0.0001147989,0.00001870385,0.002862258],"genre_scores_gemma":[0.9337252,0.000004200796,0.06513943,0.0003513965,0.0003413645,0.0001530328,0.0002409347,0.00002384734,0.00002058789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8914631,"threshold_uncertainty_score":0.9999724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4313602545002159,"score_gpt":0.4932031999261303,"score_spread":0.0618429454259144,"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."}}