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1{2  "task_id": "T3-synthesis",3  "target_definition": "theta = ln(T_AI / T_noAI): natural log of the ratio of mean task-completion time with access to a generative-AI assistant to mean completion time without it, on the same tasks, from a randomised comparison; negative = faster with AI.",4  "items": {5    "S1": {6      "estimate_as_printed": "-0.24. (ExpCon coefficient, Model 2, LogToT; marker '.' = p<.1); text: beta_1=-0.24, 'about 21%' faster",7      "uncertainty_as_printed": "SE (0.14); 95% CI = [-0.51, 0.03]; p=0.086",8      "sample_as_printed": "n = 96 (Table III caption); Section VI-B: N=47 (AI), N=46 (no AI)",9      "definition": "OLS coefficient of the experimental-condition (AI) indicator on natural-log time on task, with developer-level covariates (Model 2); RCT, one complex enterprise coding task",10      "locator": "arxiv-2410.12944v3: Table III, row ExpCon, column (2) 'Dev' (+ SE line below); Section VI-C (CI and p for Model 2)",11      "harmonisable": true,12      "harmonised_estimate": -0.24,13      "harmonised_se": 0.14,14      "poolable": true,15      "transformation": "log-time regression coefficient: theta = b = -0.24; SE(theta) = SE(b) = 0.14 (printed CI gives (0.03-(-0.51))/(2*1.96) = 0.1378, consistent)",16      "reason_if_not": null17    },18    "S2": {19      "estimate_as_printed": "+19% ('allowing AI actually increases completion time by 19%'; 'implement issues in 19% more time on average')",20      "uncertainty_as_printed": "none printed in the extract (95% CI shown only in Figure 1, not reproduced)",21      "sample_as_printed": "16 developers, 246 tasks; 136 issues AI-allowed, 110 issues AI-disallowed",22      "definition": "S = E[time AI allowed]/E[time AI disallowed] - 1, estimated as exp(beta)-1 from OLS of log implementation time on AI indicator and log forecast time (Sections 2.3, D.1-D.3); issue-level RCT",23      "locator": "arxiv-2507.09089v2: Abstract and Section 3 'Results' opening paragraph (estimator Sections 2.3, D.1, D.3)",24      "harmonisable": true,25      "harmonised_estimate": 0.1739533071,26      "harmonised_se": null,27      "poolable": false,28      "transformation": "percentage change: theta = ln(1 + 0.19) = 0.173953",29      "reason_if_not": "Not poolable: no SE, CI or p-value for the headline estimate is printed in the extract; its CI appears only in Figure 1 (and Figure 15), which is not reproduced, so SE(theta) cannot be obtained."30    },31    "S3": {32      "estimate_as_printed": "Treatment 44.29 min, Control 63.10 min, Overall 53.84 min, Improvement -29.79%***",33      "uncertainty_as_printed": "significance stars only: *** (defined as 0<p<=0.01); no SE or CI printed",34      "sample_as_printed": "181 subjects (randomised half to treatment, half to control)",35      "definition": "percentage difference in mean task duration (minutes) for Copilot vs control, holding accuracy constant (control duration predicted at treatment accuracy, Appendix B); RCT",36      "locator": "arxiv-2411.01067v2: Table 3, block 'Aggregate Results', row 'All Content', columns Treatment/Control/Improvement",37      "harmonisable": true,38      "harmonised_estimate": -0.353679435,39      "harmonised_se": null,40      "poolable": false,41      "transformation": "percentage change: theta = ln(1 + (-0.2979)) = -0.353679 (ratio of printed durations ln(44.29/63.10) = -0.353962)",42      "reason_if_not": "Not poolable: the only uncertainty information is significance stars (***, p<=0.01); SE(theta) cannot be obtained."43    },44    "S4": {45      "estimate_as_printed": "Aware 50.5 s, Control 56.9 s per email; % Time Savings 11.1",46      "uncertainty_as_printed": "p-value 0.471",47      "sample_as_printed": "Aware N=56, Control N=52 (Blind N=59 not used); 167 analysts in total",48      "definition": "percentage time saving per email (full 25-email queue) of the Aware arm (agent verdicts, rationale, agent-prioritised queue) vs Control (no AI); RCT",49      "locator": "arxiv-2511.13860v1: Section 3.3, Table 3, column 'Full Corpus', rows Aware/Control time, % Time Savings, p-value",50      "harmonisable": true,51      "harmonised_estimate": -0.1176580435,52      "harmonised_se": 0.163220592,53      "poolable": true,54      "transformation": "percentage change c = -0.111 (11.1% saving): theta = ln(1 - 0.111) = -0.117658; APPROXIMATE SE from two-sided p: SE = |theta|/z(1-0.471/2) = 0.117658/0.720853 = 0.163221 (ratio of printed times ln(50.5/56.9) = -0.119322)",55      "reason_if_not": null56    },57    "S5": {58      "estimate_as_printed": "-0.278 (Treat x Post, Output, Panel A column (3))",59      "uncertainty_as_printed": "SE (0.295) (clustered at user level); not marked significant",60      "sample_as_printed": "N 18332",61      "definition": "difference-in-differences coefficient of Italy x post-ban on GitHub Output (count of push, pull requests, PR comments, commit comments, create, issues events; users with affiliation), Pre 27/28.03 vs Post 03/04.04 2023",62      "locator": "arxiv-2304.09339v1: Table 1, panel A, row Treat x Post (+ SE line), column (3) Output; row N",63      "harmonisable": false,64      "harmonised_estimate": null,65      "harmonised_se": null,66      "poolable": false,67      "transformation": "none (not harmonisable)",68      "reason_if_not": "Not harmonisable: the effect is on output counts (GitHub events) around the withdrawal of ChatGPT access in a non-randomised difference-in-differences design, not a comparison of task-completion times with vs without AI on the same tasks."69    }70  },71  "k_extracted": 5,72  "k_harmonised": 4,73  "k_pooled": 2,74  "fe_estimate": -0.1881433287,75  "fe_se": 0.106264831,76  "fe_ci_low": -0.3964223974,77  "fe_ci_high": 0.02013574,78  "re_estimate": -0.1881433287,79  "re_se": 0.106264831,80  "re_ci_low": -0.3964223974,81  "re_ci_high": 0.02013574,82  "q_stat": 0.3236860523,83  "i2": 0.0,84  "tau2": 0.0,85  "heterogeneity_interpretation": "low",86  "pooled_significant_5pct": false,87  "pooled_pct_change_re": -17.1504048535,88  "feasibility": "complete",89  "feasibility_reason": null,90  "data_issues": [91    {92      "issue": "S1: Section VI-B prints Mean LogToT=4.6 for the AI group and 4.3 for the no-AI group while stating the AI group was faster (96 vs 114 min); the two values appear swapped.",93      "handling": "Not used; the harmonised value is the Table III Model 2 coefficient, which agrees with the text of VI-C (CI, p, 21%)."94    },95    {96      "issue": "S1: Table III caption says n = 96 whereas Section VI-B reports N=47 + N=46 = 93.",97      "handling": "Both reported as printed in sample_as_printed; no effect on theta or SE."98    },99    {100      "issue": "S1: printed SE (0.14) and SE implied by the printed 95% CI [-0.51, 0.03] (0.1378) differ by rounding.",101      "handling": "Printed SE(b)=0.14 used (first convention); CI-based SE used as sensitivity analysis."102    },103    {104      "issue": "S2: the confidence interval of the headline +19% estimate is displayed only in Figure 1/15, which is not reproduced.",105      "handling": "harmonised_se = null, poolable = false; no remembered value substituted."106    },107    {108      "issue": "S3: printed improvement -29.79% differs slightly from the ratio of printed durations (44.29/63.10 - 1 = -29.81%).",109      "handling": "Printed percentage used (theta=-0.35368); duration-ratio value (-0.35396) reported in the transformation string."110    },111    {112      "issue": "S3: uncertainty only as significance stars with a non-standard key (*** 0<p<=0.01, * 0.05<p<=0.1).",113      "handling": "Harmonisable but not poolable per convention."114    },115    {116      "issue": "S4: printed % Time Savings 11.1 differs from the ratio of printed full-corpus times (50.5/56.9 -> 11.25%).",117      "handling": "Printed percentage and its p-value used; times-based theta used as sensitivity analysis."118    },119    {120      "issue": "S4: Table 3 Malicious/Non-Malicious columns (2.8, 1.8 vs 1.9, 2.4, labelled seconds) cannot be reconciled with Full Corpus times of 50.5/56.9 s; units of those columns ambiguous.",121      "handling": "Those columns are not used; only the Full Corpus column (a unit-free ratio) enters."122    },123    {124      "issue": "S4: SE recovered from a two-sided p-value (0.471) - approximate, assumes a Wald-type test on the log-ratio scale; the Aware arm also bundles agent queue prioritisation.",125      "handling": "Marked poolable with approximate SE, flagged in transformation and report."126    },127    {128      "issue": "S5: Table 1 notes print '** p<0.5' (presumably p<0.05); row label rendered as '\\times TreatPost'; header date 'August 24, 2026' is a rendering artefact; whether Output is logged is not stated unambiguously.",129      "handling": "Value reported as printed; S5 is not harmonisable for substantive reasons regardless."130    }131  ],132  "n_input_rows": {133    "studies.json": 5,134    "README.md": 17,135    "arxiv-2410.12944v3.txt": 112,136    "arxiv-2507.09089v2.txt": 132,137    "arxiv-2411.01067v2.txt": 109,138    "arxiv-2511.13860v1.txt": 162,139    "arxiv-2304.09339v1.txt": 108140  },141  "n_analysed": 5,142  "random_seed": null,143  "baseline_unweighted_mean_theta_harmonised": -0.1343460428,144  "baseline_unweighted_mean_theta_poolable": -0.1788290217,145  "pooled_studies": [146    "S1",147    "S4"148  ],149  "sensitivity_fe_with_S1_ci_se": -0.1891067723,150  "sensitivity_fe_with_S4_from_times": -0.1896745175,151  "fe_weights_pct": {152    "S1": 57.613338254,153    "S4": 42.386661746154  }155}
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