{"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.398","table":null,"tool":null,"value":[8.9725,9.5275],"weight":1.0,"where":null}],"datasets":{"women":{"columns":null,"description":"Researchers conducted randomized policy experiment in India where, since the mid-1990s, one-third of village council heads have been randomly reserved for female politicians. The CSV data set women.csv contains a subset of this data from West Bengal. The policy was implemented at the level of government called Gram Panchayat or GP. Each GP contains many villages. For this study, two villages were selected at random within each GP for detailed data collection. Each observation in the data set represents a village and there are two villages associated with each GP.\n\nVariable Description\nGP: identifier for the Gram Panchayat (GP)\nvillage: identifier for each village\nreserved: binary variable indicating whether the GP was reserved for women leaders or not\nfemale: binary variable indicating whether the GP had a female leader or not\nirrigation: variable measuring the number of new or repaired irrigation facilities in the village since the reserve policy started\nwater: variable measuring the number of new or repaired drinking water facilities in the village since the reservation policy started","file_sha256":"3c3a97cca6fdd96f6856f7856b5f8bc786a31d1a9be78c9f610ef3070783e970","format":"csv","frame_sha256":null,"generator":null,"kind":"file","licence":"CC BY-NC 4.0","member":"data/women.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.398","level":"T2","meta":{"agent_reach":{"blocked_by":[],"dtypes":{"women":{"reserved":"int64","water":"int64"}},"named":{"outcome":["water"],"treatment":["reserved"]},"reachable":true,"rule":"magi_bench.reach/1"},"answer_format":{"figure_transform":"identity","round_to":2,"unit_scale":1.0},"answer_format_from":{"figure_transform":null,"round_to":"nearest hundredth","unit_scale":"1.0: an estimator's figure is on the gold's own scale"},"cluster":"women.csv","expected_tool":"infer.ols","family":"numerical","headline_keys":{"infer.ols":["coef.reserved"]},"naive":{"dataset":"women","treatment":"reserved","y":"water"},"native":{"answer":"9.25","keywords":["Social science","Causality","Average treatment effect","Interventional data"],"multiple_choices":null,"question_type":"numerical","reference":"Quantitative Social Science 4.3.1"},"native_id":398,"reference":{"cite":1,"note":"Caminho de refer\u00eancia inferido \u00e0 m\u00e3o.","steps":[{"args":{"dataset":"women","x":["reserved"],"y":"water"},"tool":"infer.ols","why":"Difference in means of new drinking-water facilities between reserved and unreserved GPs (OLS on the randomised reservation indicator)."}]},"reference_path":{"calls":[{"args":{"dataset":"women","x":["reserved"],"y":"water"},"tool":"infer.ols"}],"needs":[],"provenance":"hand_inferred","quotes":{},"reference_datasets":[],"source_id":null},"reference_why":"Difference in means of new drinking-water facilities between reserved and unreserved GPs (OLS on the randomised reservation indicator)."},"question":"To explore if female politicians are more likely to support policies about drinking water, please estimate the average causal effects of the reservation policy on the number of new or repaired drinking water facilities since the reserve policy started. Please round to the nearest hundredth.","requires":[],"runner":null,"sources":["qrdata.gold.398","qrdata.eval_py"],"split":"public","suite":"qrdata_socsci","tags":["econ-bench","external","qrdata","qss","numerical","reference_path","agent_reachable","naive"],"target":"agent","tool":null,"truth":"QRData gold: benchmark/QRData.json item 398 at de450af45ff7101b328bb064c6b475f73414a7ed"}