{"id":"W1970246833","doi":"10.1080/17544750.2011.544084","title":"Redress for old wounds: Canadian Prime Minister Stephen Harper's apology for the Chinese head tax","year":2011,"lang":"en","type":"article","venue":"Chinese Journal of Communication","topic":"Military, Security, and Education Studies","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Remorse; Rhetoric; Redress; Law; Prime minister; Politics; Sociology; Political science","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":[0.001693749,0.000380397,0.0002122074,0.0009226864,0.03298717,0.005177603,0.0009383032,0.0023721,0.002938501],"category_scores_gemma":[0.004806159,0.0001796615,0.0001729768,0.001056153,0.01534327,0.001922102,0.002127451,0.005045555,0.0003415507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04894869,"about_ca_system_score_gemma":0.04050825,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8357771,"about_ca_topic_score_gemma":0.9104696,"domain_scores_codex":[0.9985567,0.0002984527,0.00001754892,0.0001120845,0.0005816903,0.0004335918],"domain_scores_gemma":[0.9982588,0.0005138714,0.0001555209,0.00006762901,0.0006603931,0.0003438251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004820296,0.00002472069,0.003255609,0.00007822456,0.0000166584,0.001657767,0.5007681,0.0002625891,0.000737888,0.328546,0.1457198,0.01888453],"study_design_scores_gemma":[0.00001498002,0.00002504776,0.007124946,0.0002001139,0.00002953474,0.0006283289,0.2310771,0.0004431016,0.000984843,0.0106309,0.748741,0.0001000627],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4232571,0.007797447,0.002084769,0.1324344,0.00316527,0.00005832831,0.0000846509,0.0001137549,0.4310043],"genre_scores_gemma":[0.952173,0.001087483,0.0002423758,0.006333998,0.0001669896,0.000007078731,0.00001226582,0.00002442995,0.03995242],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1642229,"threshold_uncertainty_score":0.3551493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07461126941454956,"score_gpt":0.3735279161065123,"score_spread":0.2989166466919627,"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."}}