{"id":"W4237283281","doi":"10.32920/ryerson.14639232","title":"Good news, bad news: a snapshot of conditions at small-market newspapers in Canada","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Hungarian Social, Economic and Educational Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Oregon; University of Virginia; Université Laval","keywords":"Newspaper; Journalism; Snapshot (computer storage); Public relations; Political science; Business; Advertising","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0007136416,0.0003068849,0.0003890475,0.006014595,0.00601964,0.005051371,0.0009897,0.0005889972,0.007092754],"category_scores_gemma":[0.003744181,0.0003428166,0.0003219871,0.01364849,0.001236544,0.001633331,0.001684708,0.001204473,0.001039916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03814762,"about_ca_system_score_gemma":0.05286642,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9923084,"about_ca_topic_score_gemma":0.9965648,"domain_scores_codex":[0.9981747,0.0001080549,0.0001051671,0.0001679457,0.0006947449,0.0007493116],"domain_scores_gemma":[0.9875877,0.0007737125,0.001801493,0.00016168,0.006143098,0.003532243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002784535,0.000119657,0.7569121,0.001273182,0.0001031485,0.0019403,0.09301418,0.0001676792,0.002098163,0.001315197,0.08277571,0.06000224],"study_design_scores_gemma":[0.000004157184,0.0000285409,0.9094153,0.0001785878,0.00001726365,0.0001836027,0.05386835,0.00005874981,0.0002310941,0.00004826865,0.03590892,0.00005724958],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8768684,0.005467754,0.0002023873,0.006450021,0.0001526194,0.0002511854,0.07601625,0.0001261183,0.03446516],"genre_scores_gemma":[0.9670227,0.004518001,0.0003411205,0.001338656,0.00009183025,0.0000976138,0.01232114,0.00007092113,0.01419794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03814762,"threshold_uncertainty_score":0.2767817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03423474882603709,"score_gpt":0.2832328467984956,"score_spread":0.2489980979724585,"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."}}