{"attempt":1,"datasets":{"bowles_countering":{"description_shown":"The data aims to test whether trusted WhatsApp messages can counter COVID-19 misinformation in Zimbabwe. Partnering with Internews and Kubatana, the researchers crafted short weekly messages: Week 1 emphasized transmission and social distancing, Week 2 debunked fake cures. At the WhatsApp broadcast list level, timing was randomized: treatment groups received messages on Monday, control groups on Saturday. To measure effects, a survey was sent on Thursday. Knowledge was assessed through factual questions, and behavior through a list experiment, where respondents received either a short list (only non-sensitive activities) or a long list (the same activities plus a sensitive one: visiting others during lockdown). Broadcast lists were blocked in groups of four, with random assignment across timing (treatment vs. control) and list length (short vs. long).\n\nData variables\nResponseId: identifier for the responses from the individuals\nBehavior: number of activities the respondent participated in, coded from 0 to 5\nId: identifier for individuals participating\nList: binary variable, equals 1 if the WhatsApp broadcast list is assigned to the long experimental list\nqualtrics: binary variable indicating response mode (1 if Qualtrics, 0 if WhatsApp)\nT: treatment indicator, equals 1 if the WhatsApp broadcast list is assigned to the treatment group\nfemale: binary variable, equals 1 if the respondent is female\nc_Q4: survey question on factual knowledge about COVID-19 transmission or prevention\nc_Q5: survey question on factual knowledge about misinformation or fake cures\nKnowledge: z-score of the respondent's answers to the factual questions\nc_Q4_1: sub-item of Q4 (first option, coded 1 if correct, 0 otherwise)\nc_Q4_3: sub-item of Q4 (third option, coded 1 if correct, 0 otherwise)\nc_Q4_4: sub-item of Q4 (fourth option, coded 1 if correct, 0 otherwise)\nc_Q4_5: sub-item of Q4 (fifth option, coded 1 if correct, 0 otherwise)\nblock: randomization block (grouping of broadcast lists created at similar times)\nlength_subscribe: number of months the WhatsApp broadcast list had been active\nWeek: indicator for intervention week (1 = distancing message, 2 = misinformation/cures message)\nresponse_rate: fraction of weekly responses coming from WhatsApp per person\nWeek_id: numeric identifier for the week\nurban: binary variable, equals 1 if the individual lived in an urban district","file_sha256":"3107fc57c0d67588eccecf4788cf3600ab114f22fa27694bebd9c1892a8e5049","frame_sha256":null,"role":"agent","transforms":[]}},"epoch":1,"event":"sample_init","question":"What is the effect of WhatsApp messages on individuals's knowledge about Covid19?","question_sha256":"d45329396122f63c202f05477fb997e71196495f280086c8d2a71814a5da83f7","run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":0,"skills":[],"task_id":"causcibench_real.q174","task_sha256":"bc69f820634fb1ae0b3ab86ab5f6d02758e0b06c48c7e461970a02623146c490","timestamp":"2026-10-15T17:11:47.396379Z"}
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{"arguments":{"cluster":null,"controls":[],"dataset":"bowles_countering","fe":[],"intercept":true,"level":0.95,"se":"HC1","subset":null,"weights":null,"x":["T"],"y":"Knowledge"},"attempt":1,"cached":false,"call_id":"call_7424e73f","card_version":"0.1.0","code_version":"2925aeab2262","dataset_digests":{"bowles_countering":"ce0afeaa1f0f9b2b7f6ca76a07d3288fa4145d73a3a3d4de3128c4e148972b63"},"decided_by":"model","duration_ms":14.340416993945837,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"f1fa6c0bf3c79537929e800109fef8413aa3312f2c274c55240eba8de791a351","llm_name":"infer__ols","output_digest":"417bbc9c3403517b18b4d3f5f42913791af011708b10fb47b75bacc1ec02d4d7","rationale":"Linha de base ing\u00eanua: regress\u00e3o do resultado no tratamento, sem controles.","replay_class":"replayed","result":{"assumptions":["the conditional mean of the outcome is linear in the regressors","errors are independent across observations; their variance may differ"],"call_id":"call_7424e73f","datasets":{},"diagnostics":[{"flag":false,"name":"n_obs","note":"observations used","value":864},{"flag":false,"name":"k","note":"parameters estimated, fixed-effect dummies included","value":2},{"flag":false,"name":"r2","note":"","value":0.01641000918762292},{"flag":false,"name":"df_resid","note":"","value":862},{"flag":false,"name":"se_type","note":"heteroskedasticity-robust standard errors (HC1)","value":"HC1"},{"flag":false,"name":"n_clusters","note":"errors not clustered","value":null}],"figures":[{"ci_high":0.3904389498155496,"ci_level":0.95,"ci_low":0.12442079752648338,"derivation":{"note_pt":"","steps":[{"formula":"","result":0.2574298736710165,"terms":[{"note":"","symbol":"n","unit":"observa\u00e7\u00f5es","value":864.0},{"note":"","symbol":"k","unit":"par\u00e2metros","value":2.0}],"text_pt":"Coeficiente de T na regress\u00e3o por m\u00ednimos quadrados ordin\u00e1rios de Knowledge.","unit":""},{"formula":"ep = \u221aV_jj","result":0.06776773399135474,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":0.004592465770323018}],"text_pt":"Erro-padr\u00e3o robusto \u00e0 heterocedasticidade (HC1): a raiz da vari\u00e2ncia estimada do coeficiente.","unit":""},{"formula":"IC = \u03b2 \u00b1 c \u00b7 ep","result":null,"terms":[{"note":"","symbol":"\u03b2","unit":"","value":0.2574298736710165},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.9627198418867202},{"note":"","symbol":"ep","unit":"","value":0.06776773399135474}],"text_pt":"Intervalo de 95% de confian\u00e7a: a estimativa mais ou menos o valor cr\u00edtico da distribui\u00e7\u00e3o t de Student com 862 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.T","label":"Coefficient on T in the regression of Knowledge","se":0.06776773399135474,"unit":"","value":0.2574298736710165}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":-0.03479209051058359,"ci_low":-0.22207798977787796,"coef":-0.12843504014423077,"p":0.007241311564740516,"se":0.04771080805074566,"t":-2.6919485414631015,"term":"Intercept"},{"ci_high":0.3904389498155496,"ci_low":0.12442079752648338,"coef":0.2574298736710165,"p":0.00015566231101922333,"se":0.06776773399135474,"t":3.7987085963927507,"term":"T"}]},"tool":"infer.ols","version":"0.1.0","warnings":["4 rows were dropped because one of 'Knowledge', 'T' was missing"]},"result_for_model_ref":"fdfc8619af73975df8c048b82d26de4171c7cda1cefc2b05cf006cbf594916ef","result_sha256":"bbe34f6ded7fa43aff13dac7df815ceec47e5529eb39df470121e74271a14560","run_id":"20261015T171142Z-suite-causcibench_real-naive-d6494d","seq":2,"synthetic":false,"task_id":"causcibench_real.q174","timestamp":"2026-10-15T17:11:47.448403Z","tool_id":"infer.ols","turn_id":"call_a97f1e75"}
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