{"id":"W2560721852","doi":"10.3138/cjpe.142.000","title":"L’analyse de données secondaires dans le cadre d’évaluation de programme : regard théorique et expérientiel","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Program Evaluation","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Political 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":[],"category_scores_codex":[0.1769571,0.001098869,0.00155267,0.009866738,0.004796061,0.01674029,0.003133745,0.00326202,0.005865327],"category_scores_gemma":[0.3560762,0.001045911,0.001918302,0.009222388,0.009384679,0.01744907,0.008181283,0.005337413,0.0007182519],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01454709,"about_ca_system_score_gemma":0.01584473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02417033,"about_ca_topic_score_gemma":0.02151739,"domain_scores_codex":[0.8118446,0.137535,0.008744527,0.006575533,0.03227273,0.003027589],"domain_scores_gemma":[0.4290422,0.5097086,0.0111205,0.016337,0.03190996,0.001881763],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008482277,0.001073898,0.03334875,0.003736342,0.0004382049,0.0009991158,0.5536365,0.003305993,0.004551567,0.1055,0.004805567,0.2877559],"study_design_scores_gemma":[0.0003232926,0.00178767,0.06985722,0.01518341,0.0007258693,0.002934712,0.5851554,0.04221418,0.02378012,0.1036873,0.1536835,0.0006673849],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6429687,0.008011471,0.2517548,0.01979431,0.000423671,0.002603008,0.0008707154,0.0004548987,0.07311846],"genre_scores_gemma":[0.9140459,0.001426596,0.07812241,0.0005823847,0.0000660041,0.001029395,0.0003582687,0.000121058,0.004247952],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9854529,"threshold_uncertainty_score":0.9358497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08776847791292303,"score_gpt":0.3604229456213472,"score_spread":0.2726544677084242,"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."}}