{"id":"W2898337756","doi":"10.1080/14494035.2018.1504488","title":"Designing for robustness: surprise, agility and improvisation in policy design","year":2018,"lang":"en","type":"article","venue":"Policy and Society","topic":"Policy Transfer and Learning","field":"Social Sciences","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Surprise; Computer science; Robustness (evolution); CLARITY; Economics; Risk analysis (engineering); Business; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06468314,0.0009748241,0.0008837791,0.002492712,0.003027213,0.01112101,0.002566315,0.00443405,0.003500828],"category_scores_gemma":[0.1031182,0.000862637,0.0009271319,0.001444818,0.03423628,0.01419573,0.009738233,0.005126591,0.0004070858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007870769,"about_ca_system_score_gemma":0.006477769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001128778,"about_ca_topic_score_gemma":0.0008309868,"domain_scores_codex":[0.9230782,0.06628766,0.002214504,0.002383301,0.004266355,0.00176995],"domain_scores_gemma":[0.8357357,0.1359197,0.009837356,0.01112704,0.004937098,0.002443162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001513911,0.0001030699,0.003434419,0.0003924358,0.00007697991,0.0002409115,0.01384197,0.03961734,0.0007249955,0.8931565,0.000944422,0.04731553],"study_design_scores_gemma":[0.00004369824,0.0002013471,0.0008717664,0.0004808629,0.00003763142,0.0001482559,0.006445823,0.0214306,0.001452713,0.9542983,0.01452298,0.00006602581],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09822567,0.001800051,0.7998763,0.03115795,0.0002689899,0.0003894812,0.00003289787,0.0004804569,0.06776823],"genre_scores_gemma":[0.918853,0.0004303885,0.07839423,0.0006679785,0.00006864893,0.0002945825,0.00001303961,0.00006667841,0.001211316],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06468314,"threshold_uncertainty_score":0.3420812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05732074791790828,"score_gpt":0.3660698441419762,"score_spread":0.308749096224068,"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."}}