{"id":"W2897306483","doi":"10.1287/orsc.2018.1217","title":"Future-Time Framing: The Effect of Language on Corporate Future Orientation","year":2018,"lang":"en","type":"article","venue":"Organization Science","topic":"International Business and FDI","field":"Business, Management and Accounting","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiteit Antwerpen; Universiteit van Tilburg; Singapore Management University; Universiteit Gent; National University of Singapore; Stockholms Universitet; York University; Harvard Business School","keywords":"Framing (construction); Categorization; Sociology; Corporate social responsibility; Political science; Public relations; Business; Linguistics; History","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003680063,0.0003289601,0.0002930106,0.0009613411,0.0008865513,0.002396276,0.0005426356,0.0006770894,0.01533929],"category_scores_gemma":[0.01938242,0.0001829005,0.000574474,0.0009916887,0.001078748,0.001767438,0.001847264,0.001496146,0.0008046554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006411814,"about_ca_system_score_gemma":0.0005864643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006110846,"about_ca_topic_score_gemma":0.006574547,"domain_scores_codex":[0.9981484,0.001022116,0.00007590398,0.0002670544,0.0002530241,0.0002335674],"domain_scores_gemma":[0.9562239,0.0275799,0.01124881,0.001627409,0.0009409308,0.002379045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004037268,0.0005317547,0.964384,0.00005098868,0.0001276839,0.0001976765,0.01360033,0.0003290856,0.0009448929,0.003898918,0.0007793186,0.01475176],"study_design_scores_gemma":[0.00002127225,0.0003213551,0.9793023,0.0000898725,0.000146267,0.0000954506,0.01258494,0.001333815,0.0004767317,0.003353294,0.002243835,0.0000308848],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900168,0.0001157766,0.000420207,0.0004284904,0.00001922631,0.00001261329,0.0001156134,0.000005318002,0.008866009],"genre_scores_gemma":[0.9978467,0.00007286156,0.0002872555,0.00007147172,0.00001690187,0.00002346255,0.0001808415,0.000008028492,0.001492474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01533929,"threshold_uncertainty_score":0.05131501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005542369239064571,"score_gpt":0.224700973469019,"score_spread":0.2191586042299544,"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."}}