{"id":"W4206719805","doi":"10.5539/jel.v11n1p147","title":"Academic Inbreeding: A Risk or Benefit for Universities?","year":2022,"lang":"en","type":"article","venue":"Journal of Education and Learning","topic":"Higher Education Governance and Development","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inbreeding; Higher education; Psychology; Qualitative research; Medical education; Sociology; Political science; Social science; Medicine; Demography; Population","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006547607,0.0002852913,0.0004433615,0.0005629653,0.004446017,0.003091706,0.0007766977,0.002050625,0.003226514],"category_scores_gemma":[0.02069228,0.0002045276,0.0002200507,0.0005500978,0.005568071,0.003662271,0.003487987,0.001641885,0.0001954981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001788912,"about_ca_system_score_gemma":0.003435419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001158904,"about_ca_topic_score_gemma":0.002311531,"domain_scores_codex":[0.994146,0.004019313,0.0001526266,0.0002161625,0.0006421171,0.0008237896],"domain_scores_gemma":[0.9878309,0.00614649,0.002433345,0.0004136163,0.0009017271,0.002273962],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003993552,0.0003792207,0.1594519,0.0009975549,0.00009787326,0.006154004,0.6569178,0.0003021765,0.004939015,0.06220152,0.006284796,0.1018749],"study_design_scores_gemma":[0.00001271813,0.0003072368,0.03427552,0.000464888,0.00004737939,0.001714335,0.9364737,0.0002629352,0.0006556254,0.009013664,0.01672511,0.00004693757],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9649364,0.001307519,0.001362498,0.02301209,0.0001266632,0.00002201885,0.0000177576,0.00001511823,0.009199933],"genre_scores_gemma":[0.9985657,0.0003151097,0.0001821356,0.0004708025,0.00002798842,0.000005173723,0.000002307996,0.000001640678,0.0004293096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9934524,"threshold_uncertainty_score":0.03462744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02727375448314537,"score_gpt":0.3532087633661343,"score_spread":0.3259350088829889,"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."}}