{"id":"W4210712191","doi":"10.32920/ryerson.19100348","title":"Evaluating Non-profit Intraorganizational Twitter Use of UNICEF and MSF","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Social Media and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; McGill University; Royal Roads University; Professional Engineers Ontario","funders":"UNICEF","keywords":"Framing (construction); Rhetorical question; Not for profit; Non profit; Public relations; Profit (economics); Business; Political science; Marketing; Advertising; Economics; Business administration; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005991205,0.000354208,0.0002816992,0.003373716,0.003287747,0.003799936,0.0004980379,0.000808995,0.003874048],"category_scores_gemma":[0.03043723,0.0001932795,0.0001704307,0.003462566,0.001778665,0.004057863,0.002457513,0.0007728471,0.0005897044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00501495,"about_ca_system_score_gemma":0.002290662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09618277,"about_ca_topic_score_gemma":0.1286533,"domain_scores_codex":[0.9959434,0.002238935,0.0002149041,0.0002671624,0.0007809632,0.0005546299],"domain_scores_gemma":[0.9659791,0.02097925,0.004904895,0.00114291,0.005690603,0.001303327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006019272,0.0002712097,0.5266007,0.0004443746,0.00005452955,0.0005746071,0.4217937,0.0002192407,0.001739963,0.0025302,0.002026653,0.0431429],"study_design_scores_gemma":[0.00001340398,0.0001664384,0.4210706,0.0002021233,0.00003212846,0.0001094668,0.565436,0.0007024897,0.001030486,0.0003135374,0.01088231,0.00004108055],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904696,0.00009912802,0.0001038608,0.0002655643,0.000009838075,0.00006548195,0.0003474089,0.000004681362,0.008634444],"genre_scores_gemma":[0.9976805,0.0001346646,0.0001880725,0.00007686175,0.00001214787,0.0001156628,0.0003060808,0.00001168492,0.001474332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09618277,"threshold_uncertainty_score":0.1912459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.193522582469687,"score_gpt":0.4400497181044246,"score_spread":0.2465271356347375,"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."}}