Ipseity Daily Data

At what rate do individuals say they are X? Begining on 2025-07-08, I surveyed a small random sample of American adults on a daily cadence. They responded to many items of the form: Does <signifier> describe you today? The file ipseity-daily-aggregated.csv in this repository contains the aggregated results through 2025-07-28. The columns are as follows: signifier - a word, phrase or emoji yes_count - the number of respondents who answered yes (aggregated all-time). no_count - the number of respondents who answered no (aggregated all-time). prevalence_per_10k - an estimate of the prevalence per 10,000. If we were to survey 10,000 American adults, how many would we expect to respond yes to this signifier? The number is calculated as yes_count / (yes_count + no_count) * 10,000. earliest_obs_date - this date represents the first time this particular signifier was ever displayed to a respondent. Signifiers are chosen with stochasticity from a long list; new signifiers are sometimes added, old signifiers are sometimes deleted, and a signifier may be moved higher or lower in priority for sampling. latest_obs_date - the date closest to the present date on which signifier was most recently presented to a respondent. Version created on 2025-09-25 — cumulative data.个体自称具备X特征的比率是多少？ 本研究自2025年7月8日起，针对美国成年人的小型随机样本开展每日调研。受访者需回答大量形如「<标识词（signifier）>是否符合你今日的状态？」的问题。 本仓库中的ipseity-daily-aggregated.csv文件包含截至2025年7月28日的汇总调研结果，各字段说明如下： - signifier（标识词）：单词、短语或表情符号 - yes_count（肯定应答累计数）：所有历史应答中选择“是”的受访者总人数 - no_count（否定应答累计数）：所有历史应答中选择“否”的受访者总人数 - prevalence_per_10k（每万人流行率估算值）：若调研10000名美国成年人，预计将有多少受访者针对该标识词选择“是”。该数值的计算公式为 yes_count / (yes_count + no_count) * 10000 - earliest_obs_date（首次观测日期）：该标识词首次被展示给受访者的日期。标识词从长列表中随机抽取，抽取过程带有随机性；期间有时会新增标识词、删除旧标识词，或调整其抽样优先级。 - latest_obs_date（末次观测日期）：该标识词最近一次被展示给受访者的日期，即距离当前日期最近的展示日期。 本版本创建于2025年9月25日，数据为累计汇总结果。