{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/finding-regions-of-heterogeneity-in-decision","title":"Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance","arxiv_id":"2110.14508","date":"2021-10-27","proceeding":"NeurIPS 2021 12","authors":["Justin Lim","Christina X Ji","Michael Oberst","Saul Blecker","Leora Horwitz","David Sontag"],"abstract":"Individuals often make different decisions when faced with the same context, due to personal preferences and background. For instance, judges may vary in their leniency towards certain drug-related offenses, and doctors may vary in their preference for how to start treatment for certain types of patients. With these examples in mind, we present an algorithm for identifying types of contexts (e.g., types of cases or patients) with high inter-decision-maker disagreement. We formalize this as a causal inference problem, seeking a region where the assignment of decision-maker has a large causal effect on the decision. Our algorithm finds such a region by maximizing an empirical objective, and we give a generalization bound for its performance. In a semi-synthetic experiment, we show that our algorithm recovers the correct region of heterogeneity accurately compared to baselines. Finally, we apply our algorithm to real-world healthcare datasets, recovering variation that aligns with existing clinical knowledge.","url_abs":"https://arxiv.org/abs/2110.14508v1","url_pdf":"https://arxiv.org/pdf/2110.14508v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"finding-regions-of-heterogeneity-in-decision","repo_url":"https://github.com/clinicalml/finding-decision-heterogeneity-regions","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"causal-inference","task_name":"Causal Inference"},{"task_slug":"clinical-knowledge","task_name":"Clinical Knowledge"},{"task_slug":"decision-making","task_name":"Decision Making"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2110.14508","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.14508"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/clinicalml/finding-decision-heterogeneity-regions","reach":null}],"summary":{"ran_draft_wrong":1,"unverified":1},"by_repo_kind":{"official":{"samples":2,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":2,"samples":[{"code_sha256_prefix":"312bdba6880d7ff4","entry":"best_G","repo":"clinicalml/finding-decision-heterogeneity-regions","repo_kind":"official","path":"baselines.py","file_url":"https://github.com/clinicalml/finding-decision-heterogeneity-regions/blob/HEAD/baselines.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"312bdba6880d7ff4"}},{"code_sha256_prefix":"6cc1e9fdac7db2b3","entry":"IterativeRegionEstimator","repo":"clinicalml/finding-decision-heterogeneity-regions","repo_kind":"official","path":"IterativeRegionEstimator.py","file_url":"https://github.com/clinicalml/finding-decision-heterogeneity-regions/blob/HEAD/IterativeRegionEstimator.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"6cc1e9fdac7db2b3"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}