{"id":"W1572018399","doi":"10.1007/978-3-540-73101-6_8","title":"Job Satisfaction and Motivation in a Large Agile Team","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Software Engineering Techniques and Practices","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Agile software development; Scrum; Knowledge management; Autonomy; Variety (cybernetics); Software development; Team software process; Agile usability engineering; Job satisfaction; Computer science; Software; Process management; Engineering; Engineering management; Software engineering; Software development process; Psychology; Political science","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":[0.001807458,0.0002202529,0.0002801474,0.0006164523,0.001535762,0.001380061,0.0005243609,0.000660779,0.001568703],"category_scores_gemma":[0.004129402,0.0002558315,0.0002745957,0.0004806061,0.0007906993,0.0004387454,0.0007811159,0.001246995,0.0003789421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007668655,"about_ca_system_score_gemma":0.0008232833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008003433,"about_ca_topic_score_gemma":0.009381908,"domain_scores_codex":[0.9992973,0.0003330377,0.00002244137,0.00004652884,0.0001098875,0.0001908992],"domain_scores_gemma":[0.9943339,0.001472228,0.0005105533,0.0001014411,0.0004907733,0.003091214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002116987,0.006946041,0.9209425,0.00004240245,0.0001007164,0.002326626,0.02283593,0.001680637,0.003707469,0.001096944,0.002288274,0.03591542],"study_design_scores_gemma":[0.00006030342,0.002258244,0.9796171,0.00001314156,0.00002448461,0.000381447,0.01255969,0.003664321,0.0002960535,0.0004966746,0.0005878307,0.00004066202],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994361,0.00001767477,0.00004839514,0.00004847446,0.000004247879,0.000003364608,0.000009010591,0.000001880543,0.0004308497],"genre_scores_gemma":[0.9993916,0.000009951149,0.00005823947,0.0000128081,0.000003272783,0.000006913078,0.00001379822,0.00000174853,0.0005017419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008003433,"threshold_uncertainty_score":0.01591372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01932279094970426,"score_gpt":0.2636909671427683,"score_spread":0.244368176193064,"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."}}