{"id":"W4390576605","doi":"10.2139/ssrn.4684201","title":"A Framework for Data Representation and Use in the Digitalization Era: Speakers and Hearers in Different Realities and Settings","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Representation (politics); Computer science; Linguistics; Political science; Philosophy","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":[0.04125872,0.001212269,0.001359323,0.01033794,0.005271428,0.01891279,0.004395109,0.005043868,0.00601015],"category_scores_gemma":[0.07191444,0.001135848,0.002204315,0.009290154,0.016201,0.02155947,0.008597978,0.005626822,0.001374407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004648782,"about_ca_system_score_gemma":0.008272349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01907761,"about_ca_topic_score_gemma":0.01016361,"domain_scores_codex":[0.9690597,0.02193007,0.002530475,0.003040671,0.002458326,0.0009808299],"domain_scores_gemma":[0.9346334,0.04710857,0.002606308,0.007899578,0.005699916,0.002052328],"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":[0.00005145766,0.00006623407,0.002301633,0.0001540283,0.00004169267,0.0002029226,0.01441645,0.001493942,0.0008859333,0.9374717,0.002478099,0.04043577],"study_design_scores_gemma":[0.00003848316,0.00005699301,0.001713821,0.0004065234,0.00005852896,0.0005196921,0.01281533,0.02466068,0.001095498,0.9154428,0.0430956,0.000096075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005494083,0.0005093318,0.9756191,0.008320805,0.00009833607,0.0003280737,0.0004342343,0.0004481205,0.008747844],"genre_scores_gemma":[0.1619421,0.0004646317,0.8324702,0.0009909561,0.0001424405,0.001031623,0.000694384,0.0001891002,0.002074503],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04125872,"threshold_uncertainty_score":0.2181995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2389997754515524,"score_gpt":0.4489211331036247,"score_spread":0.2099213576520723,"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."}}