{"id":"W4416411073","doi":"10.1016/j.futures.2025.103737","title":"Yes, but…: Technology, netnography, and futures","year":2025,"lang":"en","type":"article","venue":"Futures","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Netnography; Social media; Big data; Futures contract; Vision; Social media analytics; Realm; Contrarian; Consumption (sociology)","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":[0.002803881,0.0003360821,0.0001738369,0.001096699,0.004920278,0.01108355,0.0006465526,0.002300641,0.008251021],"category_scores_gemma":[0.00550731,0.0001850847,0.0003618739,0.001052622,0.02227361,0.02332704,0.004310966,0.003908935,0.001180638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003138099,"about_ca_system_score_gemma":0.001738603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003228948,"about_ca_topic_score_gemma":0.003575007,"domain_scores_codex":[0.9985411,0.0008741161,0.00002788712,0.0001477717,0.0002008089,0.0002083702],"domain_scores_gemma":[0.9965857,0.001687754,0.0004257302,0.0002456444,0.0003277759,0.0007272734],"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":[0.00004035661,0.00003693955,0.003962667,0.0001206172,0.00001009635,0.0003799434,0.06941568,0.0002467606,0.0002695553,0.8824571,0.01281653,0.03024369],"study_design_scores_gemma":[0.00001141764,0.00006345394,0.003808495,0.0006542534,0.000009508069,0.0007124796,0.101537,0.0007043747,0.0003781328,0.6065418,0.2855123,0.00006682414],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1864635,0.02392382,0.01820754,0.203438,0.001823461,0.00005999787,0.0002142993,0.0001407977,0.5657287],"genre_scores_gemma":[0.9661785,0.005387181,0.002559356,0.004110658,0.0002845579,0.00002994211,0.00005570531,0.00004518999,0.02134881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01108355,"threshold_uncertainty_score":0.02760237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007325411273189681,"score_gpt":0.3558326368988772,"score_spread":0.3485072256256875,"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."}}