{"id":"W4414606032","doi":"10.35502/jcswb.478","title":"Digital community management for crime prevention and public safety: Strategies for safer and more inclusive online communities","year":2025,"lang":"en","type":"article","venue":"Journal of Community Safety and Well-Being","topic":"Cybercrime and Law Enforcement Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Safeguarding; Social media; Best practice; Digital media; Moderation; Community policing; Public engagement; Online community; The Internet; Community engagement","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.02830222,0.001174479,0.0009758864,0.01063668,0.01037366,0.01864712,0.005012098,0.005529996,0.0237281],"category_scores_gemma":[0.05432222,0.0005944439,0.001496707,0.005261261,0.01186269,0.03736988,0.03581056,0.005044952,0.002762643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008014578,"about_ca_system_score_gemma":0.03991486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006707118,"about_ca_topic_score_gemma":0.01349076,"domain_scores_codex":[0.981026,0.01321484,0.0007866321,0.000915361,0.002993747,0.001063532],"domain_scores_gemma":[0.9460192,0.02796553,0.004606766,0.004530659,0.006729284,0.01014862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006390241,0.0005928456,0.006442723,0.005310745,0.000125422,0.0004272434,0.03891734,0.000948869,0.0004559777,0.2622738,0.07572161,0.6087195],"study_design_scores_gemma":[0.0001129455,0.0002475596,0.005005305,0.01317453,0.00009900032,0.0003629648,0.08245642,0.001693273,0.000797016,0.2325785,0.6633701,0.000102433],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04249222,0.05537518,0.09125988,0.6123934,0.004236273,0.003493421,0.0006051275,0.001201597,0.1889429],"genre_scores_gemma":[0.5931958,0.06904468,0.2491743,0.04630462,0.002536766,0.006894203,0.001009026,0.0004000811,0.0314405],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02830222,"threshold_uncertainty_score":0.1496782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02192987546064022,"score_gpt":0.3031613748272139,"score_spread":0.2812314993665737,"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."}}