{"id":"W4414665282","doi":"10.1163/9789004322714_cclc_2022-0271-0990","title":"Making Good Green Jobs the Law: How Canada can build on international best practice to advance just transition for all","year":2025,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Best practice; Good practice; Transition (genetics); Government (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002466204,0.0001574309,0.0001553931,0.00006064706,0.001347742,0.0002054588,0.0002140584,0.0001461432,0.00001787176],"category_scores_gemma":[0.0001513613,0.0001526678,0.00004354317,0.0002414627,0.00006451387,0.000202974,0.0000273178,0.0001925295,6.427168e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008509409,"about_ca_system_score_gemma":0.0003833699,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9864825,"about_ca_topic_score_gemma":0.9997697,"domain_scores_codex":[0.9988666,0.00009310857,0.0001248698,0.0002966614,0.0002939291,0.0003248416],"domain_scores_gemma":[0.9991732,0.0002829783,0.000164912,0.0001560439,0.0001302626,0.00009261889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007742588,0.00002080891,3.552203e-7,0.00007723711,0.00002783418,0.000006584082,0.001545756,0.000002729246,4.633452e-7,0.03260496,0.9652608,0.000375039],"study_design_scores_gemma":[0.000188942,0.00009883867,0.000008370514,0.0002294217,0.00009193458,0.000003947892,0.001291897,0.000009785115,0.000002750633,0.00008306727,0.9978246,0.0001664234],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001851185,0.0001191403,0.000004456247,0.2038492,0.001232401,0.0007716037,0.7890736,0.000008930623,0.004922145],"genre_scores_gemma":[0.006514386,0.009593166,0.00007875979,0.3165871,0.009386292,0.001283544,0.6405801,0.00004528388,0.01593133],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1484935,"threshold_uncertainty_score":0.9999524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06349343297392927,"score_gpt":0.3506708839803835,"score_spread":0.2871774510064543,"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."}}