{"id":"W3032165765","doi":"10.3138/cjpe.56898","title":"Scope Creep and Purposeful Pivots in Developmental Evaluation","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Program Evaluation","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Scope (computer science); Stakeholder; Set (abstract data type); Session (web analytics); Psychology; Knowledge management; Engineering ethics; Plenary session; Process management; Pedagogy; Public relations; Business; Political science; Computer science; Engineering; World Wide Web; Library science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3511024,0.001048389,0.001491319,0.004121096,0.008679108,0.01664926,0.004233051,0.005182844,0.004000185],"category_scores_gemma":[0.3406763,0.00199693,0.00134454,0.002087638,0.05045634,0.0246926,0.02944256,0.0086393,0.0007396569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01293721,"about_ca_system_score_gemma":0.0217701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001687085,"about_ca_topic_score_gemma":0.002738351,"domain_scores_codex":[0.6176476,0.3201445,0.01557653,0.01167431,0.02780994,0.007147181],"domain_scores_gemma":[0.454653,0.4391913,0.01806446,0.05270837,0.02851466,0.006868119],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003043984,0.0002845988,0.01044973,0.001419164,0.00007515753,0.001317952,0.1833876,0.001931907,0.002920911,0.6624235,0.003662393,0.1318227],"study_design_scores_gemma":[0.0002718302,0.0006223558,0.005103697,0.004253971,0.00009239878,0.001318688,0.09124701,0.008118622,0.0082583,0.7583467,0.1221541,0.0002123277],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2268799,0.003219234,0.5781754,0.0398255,0.0007317312,0.004033775,0.0001076708,0.001094007,0.1459328],"genre_scores_gemma":[0.8940837,0.0003664837,0.09606443,0.002589636,0.00007140686,0.002722145,0.00004054236,0.000249832,0.003811814],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6488975,"threshold_uncertainty_score":0.8002062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5926935965616887,"score_gpt":0.5368839960960672,"score_spread":0.05580960046562156,"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."}}