{"id":"W2227314640","doi":"","title":"Constructing Public Space| “Legit Can’t Wait for #Toronto #WorldPride!”: Investigating the Twitter Public of a Large-Scale LGBTQ Festival","year":2016,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Gender, Feminism, and Media","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Visibility; Mandate; Diversity (politics); Queer; Space (punctuation); Public space; Advertising; Sociology; Heteronormativity; Media studies; Internet privacy; Political science; Computer science; Business; Geography; Gender studies; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002072026,0.0002983897,0.0002894731,0.001103841,0.01354926,0.008305062,0.0009244833,0.001427336,0.005783972],"category_scores_gemma":[0.005107954,0.0003909142,0.0002032288,0.001346707,0.009587829,0.005558303,0.005782634,0.001457627,0.0007837016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01071246,"about_ca_system_score_gemma":0.004937718,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1745747,"about_ca_topic_score_gemma":0.3533076,"domain_scores_codex":[0.9984146,0.0007861366,0.00002370542,0.0001444488,0.0002027715,0.000428296],"domain_scores_gemma":[0.9974805,0.000950784,0.0005117452,0.0001778766,0.0002891658,0.0005899713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00005910566,0.00003553956,0.02221325,0.00005644443,0.000006597949,0.0003851046,0.9630722,0.00003947072,0.0007270016,0.005052317,0.003855274,0.004497675],"study_design_scores_gemma":[0.000002730611,0.00001786313,0.01522159,0.00003762773,0.000003826318,0.00003250386,0.9657867,0.00007463461,0.0001297437,0.0004520636,0.01823145,0.000009170409],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686271,0.0001419632,0.0004511483,0.004019187,0.00006759217,0.00005037809,0.0002999277,0.0000240338,0.0263187],"genre_scores_gemma":[0.9954702,0.000120433,0.0001657893,0.0004658516,0.00002838158,0.00005434973,0.0001013329,0.00003972824,0.003554066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8254253,"threshold_uncertainty_score":0.3471172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3337350506887313,"score_gpt":0.5332760226871559,"score_spread":0.1995409719984246,"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."}}