{"id":"W3032198526","doi":"10.1145/3313831.3376346","title":"The Influence of Decaying the Representation of Older Social Media Content on Simulated Hiring Decisions","year":2020,"lang":"en","type":"article","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Demographics; Social media; Resizing; Representation (politics); Media content; Content (measure theory); Computer science; Internet privacy; Psychology; Business; Multimedia; World Wide Web; Sociology; Mathematics; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0005350902,0.00004732076,0.000091849,0.0000179715,0.0006913457,0.00003709306,0.0004085199,0.00004722608,0.0000232996],"category_scores_gemma":[0.008695949,0.0000275436,0.00005197372,0.0003552099,0.0002475856,0.0001623097,0.0001352695,0.0001037927,0.000005547477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002122441,"about_ca_system_score_gemma":0.00005353488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001941016,"about_ca_topic_score_gemma":0.00107973,"domain_scores_codex":[0.9988873,0.0002161902,0.0002376296,0.0001178381,0.000423367,0.0001176498],"domain_scores_gemma":[0.9976627,0.001822676,0.0001453873,0.0001547565,0.0001743714,0.00004007287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0007334704,0.0002429922,0.016821,0.00003360888,0.0001816789,0.000003569708,0.5627817,0.007505498,0.03977717,0.1975728,0.005834718,0.1685118],"study_design_scores_gemma":[0.002574665,0.0002286576,0.6508738,0.0001910602,0.0001282778,5.89149e-7,0.2296133,0.006875246,0.052192,0.04735083,0.009457792,0.0005138068],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895215,0.0000365737,0.0006982919,0.007976774,0.0001018698,0.0002751365,0.000005319837,0.00002957763,0.001354973],"genre_scores_gemma":[0.9995257,0.0001004272,0.00003864499,0.0002173193,0.00009941005,0.000004070392,0.000001956455,0.00000307696,0.000009458118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6340528,"threshold_uncertainty_score":0.9996542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1391192274786563,"score_gpt":0.3654271030543716,"score_spread":0.2263078755757153,"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."}}