{"id":"W4407398899","doi":"10.3998/mij.6807","title":"Diversity and Equity from Below: Media Worker Unions and Collective Bargaining","year":2025,"lang":"en","type":"article","venue":"Media Industries","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"World Federation of Science Journalists; University of New Brunswick; University of Toronto","funders":"","keywords":"Computer science","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":[0.01243707,0.00027722,0.0003590095,0.002261484,0.008635584,0.009544508,0.001192177,0.003081696,0.007929917],"category_scores_gemma":[0.01671778,0.0002424366,0.0004531488,0.00297242,0.01999316,0.01078287,0.007746255,0.003963753,0.0006087712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004963354,"about_ca_system_score_gemma":0.005644742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007234267,"about_ca_topic_score_gemma":0.007332296,"domain_scores_codex":[0.9856026,0.008506948,0.0004082173,0.0007552513,0.003004516,0.001722539],"domain_scores_gemma":[0.9896824,0.007897316,0.0009297763,0.0004634592,0.0005303516,0.0004967367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005184567,0.00004452465,0.004378121,0.0003464365,0.00001661407,0.0002464339,0.05597016,0.0004572592,0.000250543,0.8199739,0.00554849,0.1127156],"study_design_scores_gemma":[0.00002266477,0.00009318495,0.01260669,0.004959878,0.0000382225,0.0004750043,0.105691,0.0009185963,0.0007391364,0.4198467,0.4545481,0.00006077346],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1748748,0.08705631,0.03719336,0.07412523,0.001702332,0.0001040249,0.00007722351,0.00004949852,0.6248173],"genre_scores_gemma":[0.9519091,0.01513629,0.003373322,0.008679927,0.000929182,0.0001125862,0.00004396872,0.00005457039,0.01976113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01243707,"threshold_uncertainty_score":0.06577426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04842992486902357,"score_gpt":0.2623352182259337,"score_spread":0.2139052933569101,"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."}}