text:   Ground Truth Data",6,"['New paper! ""Equity in Resident Crowdsourcing: Measuring Under-reporting without Ground Truth Data"" w/ @ZhiLiu724 \n\nWe develop method to quantify under-reporting in @nyc311-like systems. Applying it to NYC Parks data reveals big spatial disparities \n\n<LINK> <LINK>', ""Quantifying under-reporting is tricky. Why? The whole reason these systems exist is bc we don't know  when/that incidents happen. So, if something isn't reported: is it because it didn't happen, or because no one reported it?"", 'Standard approach: Try to estimate ground truth. This is hard (and harder to validate), for same missing data reasons! \n\nOur approach: Leverage that there are sometimes *multiple* reports about the same incident, to disentangle reporting rates from incident occurrence rates.', 'Why does this matter? If there are reporting disparities, that propagates to downstream disparities in what work government agencies do, and when they do it.\n\nWe’re now working directly with Parks to understand and improve the end-to-end reporting-to-work pipeline. https://t.co/0Bg4YXaTCJ', 'We think our method can be almost directly applied to other reporting systems, like software bugs and other agency/311 systems -- please reach out!\n\nPaper link: https://t.co/vjvoOm6Nep\n\n(Virtual) talk next week 5/5 at C3ai seminar: https://t.co/X20ePSUQRj', 'And (virtual) talk this Wednesday at TOC4Fairness!\n\nhttps://t.co/yV0Xf4Yez1']",22,04,1311