{"id":"W3180934268","doi":"10.1108/jd-02-2021-0024","title":"“So many things were new to us”: identifying the settlement information practices of newcomers to Canada across the settlement process","year":2021,"lang":"en","type":"article","venue":"Journal of Documentation","topic":"Library Science and Administration","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Settlement (finance); Originality; Process (computing); Public relations; Information needs; Sociology; Information system; Knowledge management; Political science; Business; Library science; Qualitative research; Social science; Computer science; Law; Finance","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":[0.004437823,0.0003326817,0.0004141345,0.002265613,0.02036811,0.009208147,0.001673437,0.0008388446,0.003926298],"category_scores_gemma":[0.01228397,0.0003492003,0.0002601855,0.00453693,0.00954183,0.003082366,0.006107627,0.001646899,0.0002988871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03686387,"about_ca_system_score_gemma":0.07176177,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9420832,"about_ca_topic_score_gemma":0.9721707,"domain_scores_codex":[0.9968969,0.0009964714,0.000115342,0.0002969867,0.0006865179,0.001007751],"domain_scores_gemma":[0.9919655,0.002208078,0.001009789,0.0003718687,0.002505373,0.001939354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003343388,0.00001603343,0.02511061,0.00007491402,0.000005020942,0.0005762237,0.957249,0.00003962277,0.0003301883,0.0007603669,0.001016556,0.01478793],"study_design_scores_gemma":[0.000001180581,0.000009776148,0.01362754,0.00005599525,0.000003599559,0.00006524289,0.9788638,0.00004224926,0.00009530946,0.00006984211,0.007153983,0.00001150613],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879013,0.0005461135,0.0006179009,0.001926364,0.0000262009,0.00008068006,0.0001431071,0.00001930985,0.00873902],"genre_scores_gemma":[0.9946573,0.0006378372,0.0007522981,0.0002999691,0.000005375696,0.00003901863,0.0001060817,0.00001807726,0.003483956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05791676,"threshold_uncertainty_score":0.2674674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03232419148134497,"score_gpt":0.3929137670858592,"score_spread":0.3605895756045143,"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."}}