{"id":"W7081992938","doi":"10.1016/j.euroecorev.2025.105128","title":"The ins and outs of employment: Labor market adjustments to carbon taxes","year":2025,"lang":"en","type":"article","venue":"European Economic Review","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Research Grants Council, University Grants Committee; Sun Yat-sen University; Universiteit van Amsterdam; University of Exeter; University of Manitoba","keywords":"Unemployment; Carbon tax; Wage; Unemployment rate; Wage rate; Exploit; Efficiency wage","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007254472,0.0000858701,0.0001715417,0.00001722286,0.00005458965,0.00003532053,0.0005640467,0.000008351756,0.00002339666],"category_scores_gemma":[0.0001096028,0.00006203407,0.00003241137,0.00007834458,0.00002815925,0.00004151401,0.0004526052,0.00004461066,0.00004118685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000165423,"about_ca_system_score_gemma":0.0000245934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007225993,"about_ca_topic_score_gemma":0.000004490864,"domain_scores_codex":[0.9991866,0.0001520443,0.0002823792,0.0002256589,0.00002864741,0.0001246564],"domain_scores_gemma":[0.9992965,0.00006473176,0.0001031368,0.0004750155,0.00002049456,0.00004013182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001172707,0.00005099678,0.008286868,0.00258126,0.0001654554,0.00001706731,0.0003776195,0.00003757049,0.0001889737,0.03332473,0.202512,0.7524458],"study_design_scores_gemma":[0.00009288974,0.00001826644,0.01733901,0.0008689559,0.00001079403,0.000001718912,0.000005938066,0.000188208,0.0001294016,0.0003310566,0.9809365,0.00007721256],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02473249,0.09039852,0.0002522786,0.02378582,0.0004983155,0.0006567893,0.00001152849,0.00005613904,0.8596081],"genre_scores_gemma":[0.5891139,0.1686524,0.003149007,0.02102047,0.0001909135,0.00009265297,0.00000584195,0.00002196848,0.2177529],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7784246,"threshold_uncertainty_score":0.2529676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01123121774091443,"score_gpt":0.2366514396847626,"score_spread":0.2254202219438482,"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."}}