{"args":{},"checks":[{"abs_tol":null,"bind":"any","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"answer_backed","min_lre":null,"note":"every number of the answer is stated by a tool call","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":null,"value":null,"weight":1.0,"where":null},{"abs_tol":null,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":true,"key":null,"kind":"answer_figure_close","min_lre":null,"note":"QRData eval.py: strictly inside gold \u00b1 3% (a '%' gold divided by 100), on the answer figure after meta.answer_format","open_interval":true,"rel_tol":null,"required":true,"source_id":"qrdata.gold.400","table":null,"tool":null,"value":[0.062079999999999996,0.06592],"weight":1.0,"where":null}],"datasets":{"social":{"columns":null,"description":"Three social scientists conducted an RCT in which they investigated whether social pressure within neighborhoods increases participation. Specifically, during a primary election in the state of Michigan, they randomly assigned registered voters to receive different get-out-the-vote (GOTV) messages and examined whether sending postcards with these messages increased turnout. The researchers exploited the fact that the turnout of individual voters is public information in the United States. The GOTV message of particular interest was designed to induce social pressure by telling voters that after the election their neighbors would be informed about whether they voted in the election or not. The researchers hypothesized that such a namingand-shaming GOTV strategy would increase participation.\nThere are three treatment groups: voters who receive either the social pressure message, the civic duty message, or the Hawthorne effect message. The Hawthorne effect refers to the phenomenon where study subjects behave differently because they know they are being observed by researchers. The experiment also has a control group which consists of those voters receiving no message. The researchers randomly assigned each voter to one of the four groups and examined whether the voter turnout was different across the groups.\n\nThe data is in the file social.csv.\nVariable Description\nhhsize: household size of the voter\nmessages: GOTV messages the voter received (Civic Duty, Control, Neighbors, Hawthorne)\nsex: sex of the voter (female or male)\nyearofbirth: year of birth of the voter\nprimary2004: whether the voter voted in the 2004 primary election (1=voted, 0=abstained)\nprimary2006: whether the voter turned out in the 2006 primary election (1=voted, 0=abstained)","file_sha256":"3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970","format":"csv","frame_sha256":null,"generator":null,"kind":"file","licence":"CC BY-NC 4.0","member":"data/social.csv","object":null,"params":{},"path":null,"read_kw":{},"records":null,"role":"agent","sha256":"3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970","transforms":[],"url":"https://raw.githubusercontent.com/xxxiaol/QRData/de450af45ff7101b328bb064c6b475f73414a7ed/benchmark/data.zip"}},"difficulty":"M","id":"qrdata_socsci.400","level":"T2","meta":{"agent_reach":{"blocked_by":["no_reference_path","needs_op:derive_affine"],"dtypes":{},"named":{},"reachable":false,"rule":"magi_bench.reach/1"},"answer_format":{"figure_transform":"identity","round_to":3,"unit_scale":1.0},"answer_format_from":{"figure_transform":null,"round_to":"nearest thousandth","unit_scale":"1.0: an estimator's figure is on the gold's own scale"},"cluster":"social.csv","family":"numerical","gold_defect":"age year: the gold computes age from 2008 while the question fixes 2006; unpassable as worded","gold_deviation":{"evidence":"The question fixes age in 2006; the gold 0.064 matches age computed as 2008 - yearofbirth (the textbook's convention: 0.0643), while age 25 in 2006 gives 0.0655. Found by an independent statsmodels fit before any MAGI tool ran. At the question's age, 0.0655 rounds to 0.066, outside the open interval: the item is unpassable as worded (B-join review).","kind":"unverified"},"headline_keys":{},"native":{"answer":"0.064","keywords":["Social science","Causality","Heterogenous treatment effects","Interventional data"],"multiple_choices":null,"question_type":"numerical","reference":"Quantitative Social Science 4.3.3"},"native_id":400,"reference":{"cite":1,"note":"Sem caminho de refer\u00eancia com as ferramentas registradas: needs_op:derive_affine. A resposta n\u00e3o cita estimativa de efeito.","steps":[{"args":{"dataset":"social"},"tool":"data.describe","why":"Sem caminho de refer\u00eancia com as ferramentas registradas: needs_op:derive_affine."}]},"reference_path":{"calls":[],"needs":["needs_op:derive_affine"],"provenance":"none","quotes":{},"reference_datasets":[],"source_id":null},"reference_why":null},"question":"What is the average causal effect of the Neighbors message on whether the voter voted in the 2006 primary election if the voter's age was 25 in 2006? Please estimate a linear regression model with both message and age as predictors, and round the result to the nearest thousandth.","requires":[],"runner":null,"sources":["qrdata.gold.400","qrdata.eval_py"],"split":"public","suite":"qrdata_socsci","tags":["econ-bench","external","qrdata","qss","numerical","no_reference_path"],"target":"agent","tool":null,"truth":"QRData gold: benchmark/QRData.json item 400 at de450af45ff7101b328bb064c6b475f73414a7ed"}