{"id":"W7115811692","doi":"","title":"Are we getting through? Content analysis of Canada Revenue Agency media clippings","year":2010,"lang":"","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Media Influence and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Agency (philosophy); Content analysis; Revenue; Frame analysis","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004150505,0.0005809719,0.001377001,0.0004424092,0.0008832926,0.00007786772,0.001344513,0.0009087753,0.07502584],"category_scores_gemma":[0.0005521213,0.0006954516,0.0006446049,0.003540456,0.0005089887,0.0004755874,0.0001344014,0.001066864,0.00001681816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005513214,"about_ca_system_score_gemma":0.002735339,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6934506,"about_ca_topic_score_gemma":0.9853672,"domain_scores_codex":[0.9954708,0.0004538838,0.0008972915,0.0008056185,0.001313534,0.001058868],"domain_scores_gemma":[0.9947971,0.0006053825,0.002677081,0.0005493349,0.0008560176,0.0005150489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004676465,0.0004301204,0.1715943,0.002413662,0.01092163,0.001479879,0.627315,0.0005371662,0.001757818,0.01995277,0.01029316,0.1528368],"study_design_scores_gemma":[0.0005079189,0.00003457936,0.02287162,0.0007395152,0.005196366,5.285988e-7,0.2812941,0.00009923003,0.0004126089,0.000201337,0.6877563,0.0008859254],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.6088338,0.0005996033,0.00006793829,0.0009873537,0.004179927,0.000634891,0.001040531,0.00003295326,0.383623],"genre_scores_gemma":[0.2670597,0.001715737,0.0003275957,0.000681851,0.0006335279,0.000002798774,0.0003551818,0.00005650965,0.7291672],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6774631,"threshold_uncertainty_score":0.9995497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04845945662024886,"score_gpt":0.2690683280442675,"score_spread":0.2206088714240186,"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."}}